Human Social Complexity -CANCELLED- Cultural Consequences fall 2011
ANTHRO 174AW HUMAN COMPLEXITY lec A (#tba) 12:30-1:50 SST 155 Instructor: Doug White Office Hours 2:30-3:30 Soc Sci Gateway 3544 3rd floor x4-5893 TA: Tolga Oztan
This is an undergraduate science-writing class on human complexity (suggested prerequisite Soc Sci 3A). It focuses on the complex network of causal variables of early ethnographically well-described human societies in the SCCS or Standard Cross-Cultural Sample. Because human societies develop in the context of historical and spatial networks we use software that first estimates "network effects" which then allows us to study the causal relations among variables that describe and explain cultural variability. You choose a single variable or topic for study and use the *Rccs* software to compute results. We gain new understanding how and why variables predict one another in expected or unexpected ways that challenge our preconceptions. The work of different students is combined by the instructor into a graph that shows the networks and patterns of these combined causalities between the predictive variables and other specific variables or topics of study.
The writing-science focus of the class is on causality, with an objective of trying to understand cultural causality using the tools of widely used and much-applauded approach of Judea Pearl's causal graphs that combine human knowledge and inference with machine learning of complex patterns. You take time early on to choose a dependent variable you're interested in (first week, and you can change it later) for finding an explanation of how and why it varies in the sample societies (aided by our ability to produce maps on-demand with the software). Through the quarter, you research the causality of its relationships to other aspects of human cultures, and to find significant results on 'what causes what' in human societies. Your tools for the term project and paper are a database on human cultures, a literature to draw from (the 1060 published articles (1,110 since I first wrote this in the spring) on the SCCS in Google Scholar. My background -- as a creator of the database, a co-developer of the software methods, and writer on numerous social science subjects that bear on cross-cultural studies -- helps to explain why I am teaching this class. I explain to the class the background behind the SCCS, how the variables were researched and why causality is not only important but fundamental to an understanding of how the world works. Your term paper is on your own findings using the related literature you find on the web using Sccs guided search.
In week two we introduce the *Rccs* R software and probe what R does, why it is so widely used, how it works, and how to build your page for R that lists your many independent (predictor) variables and your one dependent variable which will guide R to your research results. We explore the 3 parts of the program and how R calculates causal effects. We provide guidance for how students can modify simple prototypes of the program for their own project. Hopefully that will give our students a head start so they need not spend a couple of weeks figuring out how to get what they need to do a powerpoint and write a paper on their results. For today's world of computer assisted research this course gives a powerful boost for research and the ability to produce scientific understandings of complex problems.
- Login and put your name site into Working *Rccs* models
- Chronology of class meetings fall 2011
- First Reading: for background and motivation: Simon, Herbert A. 1954. Spurious Correlation: A Causal Interpretation. Journal of the American Statistical Association 49(267): 467-479. Compute a correlation
- Second: Christian Brown and Tony Eff, 2010. The State and the Supernatural: Support for Prosocial Behavior
- Third (reports on last year's class): White, White, Ren, and Oztan 2010 Causal Inference for Multilevel Networks of Early Ethnographically Well-Described Populations
- National Science Proposal 2010 growing out of this class (2009-10) (It is "peer effects" that we study in class, a valuable approach in all fields of social, historical and biological sciences)
- Map, myths and disclaimer for forager societies -- A foragers sample will be available for next year's class.
- Send an email about the course out to students a week early.
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Course (UCI) Policies
· *DROPS:* Must be submitted by 5PM of week 2 using the WebReg system. No exceptions after week 2. No late drops or change to grade options versus exceptions after week 2.
· *ADDS:* Must be submitted by 5PM of week 3 using the WebReg system. No exceptions after week 3. No late adds after week 3
· *CHANGE: *Must be submitted by 5PM of week 2 using the WebReg system. From week 3 through 6, you must use the Student Access system to submit a request for a grade option change. No exceptions will be considered after week 6. No late grade option changes after week 6.