Southern Africans & Cattle

A Set of Microworlds for Studying Agrarian Human Living

Baba Kofi Weusijana Northwestern University, Summer 2001

Introduction

This paper describes an innovative curriculum developed to enable students to learn about traditional Southern African human life and agrarian human ecosystems. It includes computer models that allow students to research different marriage customs and create their own theories and arguments regarding which customs affords community survival and sustainability. The models and this paper can be obtained from http://www.edutek.net/Kofi/models/. The models run in NetLogo Beta 6 (Wilensky, 1999), a Java Applet/Application that can be obtained from http://ccl.northwestern.edu/netlogo/.

Background Educational Rationale

Typically, students in courses regarding Anthropology (including its sub-field Archeology) are exposed to descriptions of natural environments and human family structures that are completely different from their own experience or even their society's world view. Often a rationale for the emergence or endurance of certain family structures is not provided or impulsive explanations are given that come from the instructor's cultural background and not a scientific analysis of the environments humans have lived in. More so than most of the other sciences, ideological, religious, cultural, and political inclinations have supported unscientific anthropological research (Dr. Chanaiwa writes about this occurring in Zimbabwe, Southern Africa). Such forces also threaten to lead Anthropology away from science as an epistemological approach (Kuznar, 1997). How well a theory's purveyors use rhetoric, their social standing, or their political inclination often matters more. Certainly, the collection and analysis of physical and ethnographic evidence is an integral and respected practice. Unfortunately, physical evidence is often scarce, destroyed by decay, pillagers, or conquers. Often the passage of time, and the politics and culture of the interviewed and the interviewer, distort ethnographic evidence far from the truth.

I believe that if Anthropologists could test their theories using computerized models, that would minimize some of these problems. Reputation and argumentation skills of a theory's advocate would matter less in the face of what were the results of their models, how were the models made, and what data and assumptions were used. Anthropologists would have a laboratory to test their conjectures and get experimental data quickly. Less often would they have to build expensive bio-domes, or perform invasive observations of living people. Students could also build and experiment with these computational laboratories themselves, sizing up their own inclinations against the experts.

Why Model?

How could a computer model be any better than general theorizing? How can it help students learn? Wouldn't students just build a mathematical model of the stages and outcomes they expect based on their own theories? For instance, a model of aggregate behavior of a population of humans and domesticated animals made by a student who expects extinction will surely display that student's conjecture. However, if students could build models based on the actions of individual people and domesticated animals, the aggregate behavior of the population would be the logical consequence of the rules the student assigned to the beings in the models. The outcomes that emerge might even be surprising to the students, who would then gain insight into the misconceptions that they had held. Discussion would then turn toward what was reasonable individual behavior and environmental settings, as the emergent phenomena would be the logical, not simply imagined consequences. It is that sort of modeling exercise that I want Anthropology students to experience.

Logo, StarLogoT, and NetLogo

Over the past decade, many modeling tools have been developed for formalizing assumptions about systems and exploring the consequences of those assumptions. I eventually chose to develop my SAfri models with NetLogo (Wilensky, 1999). NetLogo, and its predecessor language StarLogoT (Wilensky, 1997), is a multi-agent-modeling language, designed to explore and construct models of complex phenomena. Both NetLogo and StarLogoT are multi-agent versions of the Logo programming language. Dr. Seymour Papert developed Logo to be a playful way for children to learn mathematics, geometry, and computer programming. In Logo, children control a graphical "turtle" by giving it commands such as "forward", "back", "right", and "left" which causes the turtles to move. The turtles can drag a "pen" behind them, thus drawing as they move. StarLogoT and NetLogo are multi-agent versions of Logo and can have thousands of turtles or "agents" in one program called a "model." When a selected set of agents are given a command to move they all move in parallel. Dr. Uri Wilensky, a former student of Papert, developed StarLogoT for Macintosh computers. NetLogo was also developed by Dr. Wilensky as the next generation multi-agent language that would be more accessible (over the web and on many different computing platforms), and more useful for scientific analysis. In addition to the turtle agents, StarLogoT and NetLogo users can create different "breeds" of agents. People have made agents that are sheep, molecules, planets, and even concert attendees lining up to go to the bathroom. By default, there are special agents called "patches" that do not move. They serve as the pieces of a background grid the turtle agents walk on. Patches are usually used to model the medium or environment in which the turtle agents operate, such as the street and ground cars roll over, or the fluid molecules float in (Wilensky, 2001).

Wolf-Sheep Predation Models and Southern African Anthropology

Both StarLogoT and NetLogo have sample models. One of these is the Wolf-Sheep Predation Model (Wilensky, 2000) where students model a predator species (wolves) and their prey (sheep). The students give the wolves and sheep rules so that they can interact. Students are challenged to determine what conditions would usually lead to a stable ecosystem. Such systems are called unstable when they tend to result in extinction for one or more species involved. In contrast, systems are stable when they tend to maintain themselves over time, despite fluctuations in population sizes. Typically, students may give wolves and sheep energy levels that decrease when they move and increase when they eat. Wolves eat sheep, and in some models sheep in turn eat grass patches. If any sheep or wolf's energy level falls below 0 it dies. At every turn (also known as a step) each sheep or wolf has a certain chance of reproducing. This is the screen shot of the NetLogo version of the Wolf-Sheep Predation Model. On the right is the graphics window, populated by green grass (brown patches have been eaten), black and white sheep, and red wolves. The controls on the upper-left allow users to change program parameters and start and stop the model from running. The items on the lower left are three monitors (that display the number of sheep, grass patches, and wolves) and a graph plotter displaying the same information charted against time steps. Notice that the plotter shows the macro-level effect of hundreds of individual agents. Each agent is following the rules set for their breed. This is a graph from one of the wolf-sheep predation models a student made. The student managed to get these sorts of population swings that are also observed in the wild. As the predators eat the prey, the prey's population decreases to the point where the predators begin to starve. As wolves die out more sheep prey survives. Thus, the population graph looks like overlapping sine waves. Typically in biology classrooms, only the macro-level is taught, the micro-level interactions is often left up to the imagination. With this modeling tool, one can discover the rules that govern the micro-level, and thus provide a rationale to macro-level behavior observed in the real world. Students who participate in this discovery process are more likely to remember the experience, and the lesson it teaches, than compared to a lecture. If the macro-level behavior was all that's known about wolves and sheep, we could still make an educated argument about the micro-level, individual agent activity, based on the model (Wilensky, 2000). I sought to provide these same benefits to Anthropology.

I decided to create models similar to the Wolf-Sheep Predation Model to simulate traditional Southern African life. I postulated that such models would give Anthropology students a unique laboratory to test anthropological and social science theories about human customs and ecosystems.

The SAfri models I designed drew on my experience as a student at the University of Zimbabwe in 1995. There I took an Anthropology course (which lasted the entire year) and went on many field trips around the country and visits to museums. I learned a great deal about the Bantu-speaking peoples of Southern Africa, including about their marriage customs.

Audience and Learning Goals

My target audience is college students taking an Anthropology course or a course on Southern Africans. By engaging in activities with my suite of models (which I call the Southern Africans and Cattle models or SAfri Models for short), and under guidance from a professor, students should be able to: - Articulate the challenges of agrarian human life. - Articulate the traditional family structure of Southern Africans and make an informed argument about how well that structure affords community survival and sustainability.

Rationale for Using NetLogo: Design Goals

I originally started working on my models in StarLogoT. Later I converted them over to NetLogo models because NetLogo is the better at achieving the following design goals: * Cross-platform availability: StarLogoT is an application that runs on Macintoshes only. NetLogo is a Java application and applet that runs on most personal computers

available today. * Accessibility via the World Wide Web: Since NetLogo is an applet it can be run in web pages. Thus people can use my models without downloading and installing NetLogo onto their computer. * NetLogo has certain features that afford scientific research and are not in StarLogoT, namely: The "Behavior Space" tool that allows users to compare model runs in a scientific manner. The ability to handle larger numbers Improved computational accuracy and precision The ability to export data to text files usable in Microsoft Excel * Easier debugging: NetLogo detects errors in the LOGO code a programmer writes and automatically directs the programmer's cursor to the line where the problem was discovered. This feature along with a find utility speeds the process of developing models that work and work well.

General Design

The SAfri Model suite I created explores the stability of ecosystems that involve agrarian humans and domestic animals. These models are greatly extended from the basic design of the Wolf-Sheep Predation Model.

The SAfri Models include grass, along with human and cattle breeds. The models have the following rules for their agents:  Each breed has male and female genders and shapes.  Humans and cattle move around on the grass, eating, and reproducing.  Humans can eat grass as well as eat and herd cattle.  Each agent has a certain amount of energy which gets used up as they move, grow, reproduce, etc.  Humans also cultivate the grass, which grows a little faster about a week after they have been on it.  Energy is replenished if an agent eats or a patch of grass grows due to sunlight and/or human cultivation.  If a turtle agent's energy level is zero or below it dies.  If an agent gets too old it might die of old age.  Even when a patch of grass is eaten it begins to grow again.  If all of the humans or cattle die the model stops running.  Humans only eat cattle when they are very hungry (when they have less than 30 days of energy left).  In most models humans only have sex with their spouse.  Humans can only get married when a dowry is paid in cattle. Figure 1: A Screen Shot of a Safri Model

To allow the population to continue each female human or cattle has a fixed probability of attempting to be impregnated. In most models, female humans only attempt to get pregnant with their spouse. Marriage occurs only if a dowry of cattle is paid which is a general traditional custom among the Bantu-speaking peoples of Southern Africa (Krige, 1981). I use the term "dowry" because it is a term that is commonly known in US English. However, the term is inaccurate since it implies a payment by the bride, when in Bantu-speaking societies the groom or his family usually pays it. I also use the term

"dowry" because in one of my models the bride's family pays it. There are many Bantu and English terms for the practice of the groom or his party making some dowry payment. See Chigwedere, 1981 page 2 or Kyewalyanga, 1978 page 51 for more information.

In my models, human ownership of cattle can be visually tracked by switching to a mode that color codes each family and the cattle they own.

Students can analyze the models under the following human family structures: - Polygyny including: Polygamy: 1 Male marrying with many females Polyandry: 1 Female marrying with many males Any combination (no marriages) - Monogamy: 1 Male marrying 1 Female Virtually all Southern Bantu-speaking peoples traditionally practice some form of polygyny (Krige 1981).

The rationale for these family structures being modeled is to explore the theory that marriage customs in agrarian societies are not only based on the value placed on male or female labor, but also on how many children a community needs to be stable or growing. High mortality rates for children under 5 years old (compared to industrialized societies) and the need for many relatives to work the farm and herd cattle might have led to the traditional polygamy family structure of most Bantu-speaking peoples. Exploring and comparing what conditions in each model afford stable or growing populations will help students become informed debaters around that theory.

The text placed in the “Information” tab panel contains all the non-programming help the student needs from the software. Other assistance is expected by the professor or teacher assistant. The rationale for providing help in that manner is to give the student freedom to explore their microworlds at their own pace without a prescribed process besides the recommended sequence of models. I also want to give professors room to tailor the use of the models for their particular courses.

Critical Issues

I have purposely backgrounded the issues of societal valuation of male and female labors in favor of foregrounding the issue of societal valuation of children’s eventual contribution to a community. This is because I believe dowry is paid to a bride’s family not primarily for her labor, but for her powers as a bearer of children and personality qualities that afford good parenting. Enrichment of a family is not measured in female labor as much as in the quantity and quality of all the family members. A large, responsible, family can till more land and herd more cattle. This theory is also based on the notion of some that traditionally the dowry is considered a obligatory gift to the bride's family from the groom's family more than a purchasing fee. Furthermore, it is not the wife that is being purchased, but her services (Chigwedere, 1982, p. 3). This includes the groom's family having legal ownership of children the wife bears. In some societies, additional dowry is often given to the wife's family long after the marriage occurs, particularly in times of hardship. It is usually paid in cattle (or other livestock such as goats) because they help provide stability, since they produce milk and can be eaten in times of drought.

I have also backgrounded many details of Bantu-speaking peoples’ life, including courtship, commerce, politics, kinship relations, etc. This was to keep the already complicated models as simple as possible, while still covering the learning goals.

Course Activities and Pedagogical Guidelines I expect most professors to follow this procedure: Start with the model where mating occurs without marriage. Students familiarize themselves with the agents, code, and behaviors in the model. They play with the settings with the goal of stability in mind. Professors are encouraged to have this done in class or labs so students can ask questions and get technical help. Students then move on to models (either at home or in a lab) that include marriage, again trying to adjust the settings to achieve stability. Professors are then encouraged to have a discussion session or presentation of stabilized models. Assuming competent technical support is available and that the students have been trained in NetLogo model development, a professor might also have the students try to change models so that they afford certain family structures. Minor changes mentioned in the information tab should also be attempted.

Professors should assist their students in making sure that any macro-level behavior is an emergent phenomenon of the actions of the individual agents. There should be little central control or "fixing" or the behavior to produce desired outcomes. Each individual agent should follow a set of programmed rules that make sense for the type of people under study.

Results of Running Models

What follows on later pages are three graph plots and tables of data, one for each of the models that include marriage practices. Each set of model data is the average from ten individual runs starting from the default settings. These defaults are: Initial number of cattle 25 Initial number of humans 21 (10 men, 11 women) Grass grows? TRUE Grass caloric growth per step 1000 Cattle metabolism 25 kilo-calories per day Human metabolism 3 kilo-calories per day Maximum kilo-calories per grass patch 20 Number of steps per day 3 Mean dowry price 2 cattle Watch ownership? FALSE Cattle impregnation rate 20% Human impregnation rate 20%

Table 1: Safri Model Default Settings

The No-Marriage Model: I did not bother to present data from the no-marriage model because it is only a demonstration model whose behavior becomes very unrealistic quite rapidly. In that model the human population increases extremely fast along with the death rate as people have too many children and clump into populous communities where most die young of starvation. Often the humans eat so much of the food source that all the cattle die.

The Polygamy Model:

SAfri Polygamous Plot

Population 80

0 xcor 16 32 49 66 83 99 116 133 150 166 183 200 216 233 250 267 283 grass 146.1 41.7 192.5 181.2 174.3 168.3 165.2 157.4 162.6 154 156.2 139.4 146.6 144.4 141 141.4 138.3 134.6 cattle 25 25.7 27.1 28.2 29.7 31.1 32.9 34.6 36.2 37.6 39.4 41 42 43.9 45.8 46.7 48.1 46.9 humans 21 21.2 21.7 22.4 23.1 23.9 24.6 25.6 26.8 28.3 29.3 31.4 33.4 36.5 39.2 43 46 50 Steps Mean Male Wealth = 2.2 Cattle Figure 2: SAfri Polygamous Plot Step 300 Number of cattle 46.7 Number of humans 54.3 Number of women 27.4 Number of men 26.9 Number of married women 23.3 Mean human energy level 420.313233 Mean cattle energy level 451.607728 Mean male wealth in cattle 2.20096354

Table 2: SAfri Polygamous Model values at the 300th Step

Notice in the polygamous model's population plot (Figure 2), the human population overtakes the cattle population at about step number 270. Please also note that the grass was being driven to extinction until about step 30 when cultivation of the land began to improve its growth rate. The more people around to seed the land, the more the grass grows. This is an essential interaction needed to analyze agrarian peoples. If it were not for the need for many humans to cultivate the land, each new child could be an unwanted burden to the environment. Cultivation of the land by many people is part of the reason the polygamous model is stable.

The Polyandry Model: SAfri Polyandry Plot

0 xcor 16 32 49 66 83 99 116 133 150 166 183 200 216 233 250 267 283 grass 151.7 46.9 188.7 177.6 182.4 183.6 176.4 169.5 147.2 155.6 155.8 142.8 143.4 143.9 135.3 139.6 125.9 122.6 cattle 25 25.4 26 26.7 27.4 28.8 29.9 31.3 32.6 32.7 33.8 35.4 36.4 38.3 39.7 40.2 42.4 43.7 humans 21 21 21 21 21.3 21.3 21.3 21.3 21.4 21.4 21.4 21.4 21.4 21.4 21.4 21.6 21.7 21.7 Steps Mean Female Wealth = 4.32 Cattle Figure 3: SAfri Polyandry Plot

Step 300 Number of cattle 45.5 Number of humans 21.8 Number of women 10.6 Number of men 11.2 Number of married men 7.9 Mean human energy level 956.538108 Mean cattle energy level 563.539461 Mean female wealth in cattle 4.32212121

Table 3: SAfri Polyandry Model values at the 300th Step

In this model, the cattle population always exceeds the human one. This is because fewer children are being born compared to the polygamous model. Notice that there is also slightly less grass in this model. This is due to fewer people cultivating the land.

The Monogamy Model: SAfri Monogamous Plot

0 xcor 16 32 49 66 83 99 116 133 150 166 183 200 216 233 250 267 283 grass 145.8 42 199.1 180.7 185.5 174.1 178 164.8 154.1 158.4 154.3 156 155.5 155.7 149.3 153.7 151.3 148.4 cattle 25 25.7 26.7 27.3 28.4 29.2 30.9 32.4 33.3 34.9 36.5 37.8 39.3 40.7 40.9 42.8 44.7 47.1 humans 21 21 21.2 21.4 22.3 23 23.5 24.1 24.9 26 26.8 27.8 28.7 29.8 32.2 33.1 34.4 35.5 Steps Mean Male Wealth = 2.89 Cattle Figure 4: SAfri Monogamous Plot

Step 300 Number of cattle 49.2 Number of humans 36.8 Number of women 19.7777778 Number of men 17.022222 Number of married people 22.6 Mean male wealth in cattle 2.89033943

Table 4: SAfri Monogamous Model values at the 300th Step

In the monogamous model, the cattle population still exceeds the human population, yet the human population shadowed it by increasing at about the same rate. This seems to be a consequence of the cattle indirectly benefiting from the increase in cultivation as the human population increases.

Analysis of Model Run Results At the default model settings, different family structures can be favored based on what are the most desired outcomes.

If the maximum number of people (and therefore more assistance with cultivation and other chores of farming) is the first priority, the polygamy family structure seems superior to the others. It has the highest number of people at the 300th step, namely 54.3, a 258% increase from the original 21. This is followed by the monogamous model (with 36.8 people), and then by the polyandry model (with 21.8 people).

The polyandry model is favored if one wants small families, each wealthy with an abundance of cattle. In fact each female-headed family in the polyandry model are almost twice as rich as each male-headed family in the polygamy model. This is due to fewer children being born and higher food availability for the cattle. In addition, both humans and cattle are better fed in the polyandry model compared to the polygamy model. It is not hard to argue that people and cattle in the polyandry model have the highest quality of life.

Of course, one could argue that the monogamy model is a happy median between the other two models. The essential issue is judging what was best for the Bantu-speaking peoples is how fragile is a small community. If a small community is at too great of a risk of being eradicated by a catastrophe (such and drought) then the societies that produced more children would tend to survive more than the others do. If this is true, than the payment of a dowry to the bride's family is a very fair and prudent practice. I believe what is being gladly purchased is not just labor, but much more importantly the ability to produce new people. This theory also provides a partial explanation to why most the Bantu-speaking societies were polygamous ones. Summary and Conclusions

The SAfri models I developed, based on the Wolf-Sheep Predation Models, to simulate traditional Bantu-Speaking African life seem very useful for letting students explore different family structures, environmental settings, and their consequences. Professors can use my models as a means for initializing intelligent discussion and providing a laboratory for providing evidence for or against theories.

At the default settings, the polygamous family structure afforded more children, therefore more people, and thus more cultivation of the land. The polyandrous model afforded smaller yet richer families. The monogamous model was a median between these extremes.

Future Design Research In future, I hope to improve the environmental setting the humans and cattle operate within by making it more realistic. I want to create a village where humans live and cattle are stored during the night, farming land where food for humans grow, and grazing land where cattle eat grass as they do now. It will occasionally rain and water can also be retrieved from a river.

Figure 1: Future design of patches. Then I can have people and cattle go through daily activities. I would also add life cycle behavior, where children are born dependent on their parents and community and grow into maturity as they are nurtured and educated by their family. This will allow me to introduce age and gender division of labor issues into the analysis. I will add occasional calamities such as drought and perhaps plagues. This will allow me to more directly prove my theory, that small societies will tend to fail surviving calamities more than societies failing due to labor problems. It may be wise to start from scratch and build entirely different models to investigate these issues, since the current models are already very complex. References Chanaiwa, David. (1973) The Zimbabwe Controversy: A Case of Colonial Historiography. Syracuse, New York. Syracuse University

Chigwedere, Aeneas. (1982) Lobola – The Pros and Cons. Bulawayo. Belmont Printers

Krige, Eileen Jensen. (1981) A Comparative Analysis of Marriage and Social Structure among the Southern Bantu. In Krige, Comaroff (Eds.) Essays on African Marriage in Southern Africa. Johannesburg. Juta and Company Limited

Kuznar, Lawrence A. (1997). Reclaiming a Scientific Anthropology. Walnut Creek, California. AltaMira Press

Kyewalyanga, Francis-Xavier S. (1978). Marriage Customs in East Africa. 2nd Edition. Freiburg. Renner Publication

Wilensky, U. (1997). StarLogoT. Evanston, IL: Center for Connected Learning and Computer-Based Modeling, Northwestern University. http://ccl.northwestern.edu/cm/starlogoT/.

Wilensky, U. (1999). NetLogo. Evanston, IL: Center for Connected Learning and Computer-Based Modeling, Northwestern University. http://ccl.northwestern.edu/netlogo/.

Wilensky, U. (2000). Modeling Nature's Emergent Patterns with Multi-Agent Languages. Evanston, IL: Center for Connected Learning and Computer-Based Modeling, Northwestern University. http://ccl.northwestern.edu/uri/public_html/papers/MEE/.

Wilensky, U. (2001). Emergent Entities and Emergent Processes: Constructing Emergence through Multi-Agent Programming. Presented at the Annual conference of the American Educational Research Association, Seattle, WA: April 13, 2001 http://ccl.northwestern.edu/uri/public_html/papers/AERA/