Anthropological Methods and Models 2008

From InterSciWiki
Jump to: navigation, search

Spring 2008 Anthropological Methods and Models ANTHRO SEM 289 (60752)

UCI 3030 Anteater I&R Bldg (the building's code is AIRB), UCSD 260 Galbraith Hall

Covers problems in ethnography, archaeology, networks, organizational and longitudinal study with extensive use of the interactive Interdisciplinary sciences wiki which doubles as a home page and contains the syllabus. Open to enrollment from UCSD and UCI, and meets Fridays, 9-12, at UCSD with students enrolling through UCI. Videoconferenced with UCI if there is additional UCI graduate student enrollment (Social Science, Merage School encouraged).

The InterSciWiki:Community Portal has further entries what will be activated dependent on the specialties of students enrolled.

use QuickStart for instructions on login, create "new account" under your full name, check out the navigation pages and its "random pages" to get a flavor of whats in the wiki overall. Our seminar links to a small proportion of pages but use the "search window" to browse topically and not the indexing at the bottom of each page WikiSysop 16:03, 27 February 2008 (PST). Sample student page here: Celia de Jong -- such links are created by [[Celia de Jong]] for example. Put your link here.

Suggested topics from Geoff Braswell, UCSD, for Anthropology students

Dear Doug, Great! Thanks for doing this. Some ideas for basic topics include:

*sampling procedures, 
*data "cleaning" --- see Coding relational and attribute field data, below
*hypothesis testing, *correlation, *linear regression and 
*other basic modeling procedures (DW: Those are in the first set of topics below - 

Multiple working hypotheses). I think that would probably be enough for now Cheers -- Geoff; possibly

  • multivariate factor analysis and the like might be too much.

Ashwin's two cents

I would be game for multivariate analysis if feasible ! ~AB

in any case, here are two refs: Doug 07:55, 28 February 2008 (PST), we'll work it in or not as others wish. 

What software do you folks have on your pc or have access to? Spss? Anybody use R? R for statistical research

Another question -- AB 05:13, 6 March 2008 (PST)

Regarding the spring methods course, I'd like to get a sense of the structure of the course: lecture? discussion?, practicum w/ software/technology? or a mix? reading load or assignment load? Could you please clarify. I did not see this info on the syllabus. BTW, I had added a few books on social network to the participant list. -- Am adding that below Doug [ 06:37, 6 March 2008 (PST)

Thanks Doug!- Ashwin

John's Suggestion

Ashwin told me about Social Network Analysis and it seems like a method worth knowing something about. Here's a good website on the topic: http://www.insna.org/ -- John, thats covered in "Coding attribute and relational data" below Doug 06:33, 6 March 2008 (PST)

Yong Ming Kow's Current Research

User:Yong Ming Kow

Laurent Tambayong's Current Research

User:Laurent Tambayong

registered/photo page

A289 photos UCSDgrad Anthro Erez Ben-Yosef Sarah Baitzel Alicia Boswell Ashwin Budden Celia de Jong John J. McGraw Karen Nickels Megan Pitcavage Beth Plunger Andrew Somerville Laurent Tambayong IMBS Yong Ming Kow ICS Catherine Forsman ICS - Auditing Carolina Berys undergrad

Textbooks: for background

I Probability theory, the formal language of uncertainty, and basis for statistical inference
Read: Ch. I:1-86
II Statistical inference, the inverse of probability: Given the outcomes, what can we say about the process that generated the data?
Read: pp 87-96-118
III Applications: regression (pp 209-230), graphical models (pp 263-290), causation (pp 251-262), curve estimation (pp303-326, smoothing (pp 327-348), classification (pp 349-380), and simulation (pp 403-424).

Structure of the course

Materials and readings of the wiki, read and presented sequentially by students to begin discussion, provide basic ways and means for thinking and implementing fundamental approaches to research questions, data collection and analysis, visualization and qualitative understanding, thinking about alternative hypotheses and about theory in anthropology and the social sciences. There are truly fundamental concepts to discuss here that are not well represented in anthropology as a research discipline. Students should also develop their own topics and projects for which the ideas in this seminar can serve as a sounding board and use these as a basis for questions posed by the seminar materials in a term paper. There is a strong emphasis here on benefits from access to and simple tutorials for using available no-cost software. These will be of immeasurable value for all sorts of future projects that you may carry out, as will the emphasis on means of visualizing your data. Not the least will be the ability to use network data construction for visualization, qualitative insight, and measurements that almost invariably prove significant in advancing a research project. The basic approach taken here is that of construction: research as a constructive process involving how to see more deeply into your research problem, entertain alternative perspectives that will help to develop fundamental concepts and develop and test hypotheses that go to the heart of the the issues in your research. On the analytic side, some practicum is provided in the form of exercises guided by tutorials, and we will cover how to do some of these in class. There is also some fundamental rethinking about what is a model, an explanation, and how we test our models. If I were a graduate student in any of the variety of areas in anthropology, this is a seminar that I would not want to miss as it would inform how I can most effectively think about and carry out my research. Very little of what is presented here is to be found conventionally in how methods and models have been taught historically in anthropology, although some conventional references are provided. The ability to construct your own pages and formulate discussions on the wiki and benefit from the materials on this site are another unusual aspect of this course, and modifications/uploads to this wiki site can be done even while in class. Active engagement is easy and encouraged.

If I don't have data of my own yet, will there be some data provided that I can use?
We have plenty of data if you dont have your own
How big is this "project" (20 pages? 50?) and will I have to do every type of statistics, or do I just run the most pertinent tests (and is there a minimum required)?
only those statistics that are appropriate -- 12-14 pages
Any guide to paper-writing?
see Ten Lessons in Clarity and Grace
Will students take turns making presentations, or will they have to make one every week?
roughly three during the quarter, one on your project
Time the seminar will absorb
No more than the average

Linked Seminars

Some may be interested in the CSE seminar series at UCSD week 1

Day 1 (4-5:30 Computer Science & Engineering (CSE) Building, Room 1202): {http://intersci.ss.uci.edu/wiki/index.php/University_of_California_Complexity_Events#HSC_-_UCSD_only_Videoconference_Friday_April_4_2008_KEMP the talk by Charles Kemp this afternoon]. Abstract: Despite recent advances in machine learning, the human child is still the best learning system on the planet. I will discuss three principles that help to explain how human knowledge is acquired: learning can be guided by rich prior knowledge, learning can take place at multiple levels of abstraction, and learning can allow structured representations to be acquired. The Bayesian approach to learning can capture all three principles, and Bayesian models have been used to explore many aspects of cognition, including word learning, categorization, and causal reasoning. I will show how some of these models address problems that are routinely solved by humans, but are difficult for traditional learning theory to handle. (check how Kemp applies these methods to ethnography in my item 31.

The goal of these and some related upcoming multidisciplinary CSE seminars is to promote the development of theory and experiments that apply the theories and methodologies of computer science together with the theories and methodologies of the social and behavioral sciences. The research tools are drawn from discrete algorithms, artificial intelligence and agent-based modeling, game theory, linear programming and duality, theory of communication, networks, discrete optimization, mathematical economics, econometrics, brain and behavioral experiments.

Some may be interested in the Human Complexity videoseminar at UCSD week 3, same room at UCSD 1:30

Day 3 Apr 18 (1:30-3) Norman Johnson Leadership Landscapes in Human Complex Systems

Human Complexity videoseminar at UCSD week 7, same room at UCSD 1:30

Cosma Shalizi on methods in Complexity

A289 Required readings and exercises (progressive)

A289 required readings and exercises

Topics and Readings

Sampling procedures

Multiple working hypotheses

(Statistical topics will be progressively revisited)
   * 1 Multiple working hypotheses: Required reading
   * 2 The Basics of Modeling
   * 3 Reconstruction
         o 3.1 ___Univariate Distributions
         o 3.2 ___Higher order and Nonlinear Interactions
         o 3.3 ___Bivariate Interactions
         o 3.4 ___Causal Interactions
   * 4 Illustrative types of formal models/theories

Coding attribute and relational (network) data from fieldwork, archaeological, historical and geographic sites

OUTLINE OF WHAT's IN THE URL ABOVE:

   * 1 Introduction
   * 2 Coding field data
   * 3 Generative relationships
   * 4 Generated relationships
   * 5 Recognized relationships
   * 6 Multiple relationships
   * 7 The local (egocentric) networks and the global (whole network)
   * 8 The interdependence of local and global networks
   * 9 Alternate models, e.g., genealogy
   * 10 Canonical kinship and network graphs
         o 10.1 p-graphs
         o 10.2 kin-tipp graphs
         o 10.3 Petri graphs
   * 11 Pajek, attributes# , texts, and photos
   * 12 SVG, movies, intranets and internets
   * 13 Simulations with R software
   * 14 Social structure and cognition
   * 15 Policy implications of cognitive anthropology
   * 16 Network Ecolanguage and Representation
   * 17 References
   * 2008 Steve Borgatti's Syllabus for Social Network Analysis seminar -  
          Syllabus U. Kentucky [http://tech.groups.yahoo.com/group/ucinet 
          UCInet User's group] - Install    
   * 1994 James W. Dow Anthropology: The Mapping of Cultural Traits from Field Data. Social Science Computer Review. 12(4):479-492.
   * 2007 Murray Leaf Empirical Formalism Structure and Dynamics 2(1):804-824  

Tutorials in data analysis

Topics in R

Using SPSS: Analysis and Comparison in the Social Sciences

Table of Contents !XC-BK0.doc !XC-BK0.pdf 12-10-03
1 Analysis and Comparison in Testing Theory: An Introduction !XC-BK1.doc !XC-BK1.pdf 12-10-03 4 live html links
2 Using a Database: Comparative Research with a Standard Sample !XC-BK2.doc !XC-BK2.pdf 12-10-03 5 live html links
3 How To Do Scatterplots and Maps in SPSS 10.0-13.0 !XC-BK3.doc 11-11-04 !XC-BK3.pdf
4 How To Do Cross-Tabs in Spss 10.0/11.0 !XC-BK4.doc 10-22-04 !XC-BK4.pdf
5 Statistical Analysis of Cross-Tabs !XC-BK5.doc 10-30-04 !XC-BK5.pdf many live html links
6 Reading Cross-Tabs and the Logic of Hypotheses !XC-BK6.doc 8-5-03 !XC-BK6.pdf
7 One Factor and Third Factor Tests !XC-BK7.doc 9-26-03 live html link !XC-BK7.pdf
8 The Problem of Interdependent Cases !XC-BK8.doc !XC-BK8.pdf 12-10-03
Using the single factor model / Factor analysis in R

Simple statistics and Cautionary notes

Significance - must adjust for "effective" independent N versus "noneffective" nonindependent N

Fisher exact 2 x 2 x 2

  • (to be continued)

On-line calculators

Binomial test

Correlation

References posted by participants and faculty

  • Adams, Bob new paper http://cdli.ucla.edu/pubs/cdlb.html
  • Gerber, Eleanor R. (1999) The view from anthropology: Ethnography and the cognitive interview, pp. 217-234 in Cognition and Survey Research. Monroe G. Sirken, et al. (eds.) New York: Wiley.
  • Handwerker, W. Penn Key readings on methods 1998.
  • Handwerker, W. Penn and Stephen P. Borgatti (1998) Reasoning with numbers, pp. 549-594 in Handbook of Methods in Cultural Anthropology. HR Bernard, ed. Walnut Creek, CA: AltaMira Press.
  • Ryan, Gery W. and H. Russell Bernard. (2003) Techniques to identify themes. Field Methods 15: 85-109.
  • Schober, Michael F. (1999) Making sense of questions: An interactional approach, pp. 77-94 in Cognition and Survey Research. Monroe G. Sirken, et al. (eds.) New York: Wiley.
  • Spicer, John (2005) Making Sense of Multivariate Data Analysis. Thousand Oaks, CA: Sage.
  • Tashakkori, Abbas and Charles Teddlie. 1998 Examples of Mixed Method Desgin, Chaps. 7-8, in Mixed Methodology: Combining Qualitative and Quantitative Approaches. Thousand Oaks, CA: Sage Publications.
  • Weller, Susan C. (2007) Cultural consensus theory: Applications and frequently asked questions. Field Methods 19: 339-368.
  • White, Doug - A recent talk at the AAA, http://eclectic.ss.uci.edu/~drwhite/pw/AAA07D_WHITEpaper1c.pdf

on modeling (probably not what you expect)

Peter Carrington, John Scott, Stanley Wasserman (Eds.) 2005. Models and Methods in Social Network Analysis (Structural Analysis in the Social Sciences)

  • Wasserman, S. and K. Faust, 1994, Social Network Analysis. Cambridge: Cambridge University Press.
  • Ulrik Brandes, Thomas Erlebach. 2005. Network Analysis: Methodological Foundations.
  • John P Scott. 2000. Social Network Analysis: A Handbook. SAGE Publications; 2nd edition.
  • Alain Degenne, Michel Forse. 1999. Introducing Social Networks (Introducing Statistical Methods series).

Links, eJournals, eDownloads

Anthropology journals (online)

Journal of Quantitative Anthropology JQA & JQA contents by author
Structure and Dynamics contents eJournal of Anthropological and Related Sciences
World Cultures - World Cultures

Sociology journals

Journal of World Systems Research
Journal of Social Structure

Tutorials

Methods-R-us Jeffrey Johnson NOW AT MethodsMall
Robert Hanneman network tutorial

Virtual departments and Invisible colleges

Other Courses 2007-08, including Human Complex Systems (HCS)

A new style of teaching?
Undergrad, UCI, Fall 2007: Human Social Complexity and World Cultures
Grad Seminar, UCI, Fall 2007: Network Theory and Social Complexity
Undergrad, Grad: UCI, Fall-Winter-Spring 2007-2008: Course: social networks & complexity
Grad Seminar, UCI, Spring 2008 (taught at UCSD, UCI students by interactive video): 
  Anthropological Models and Methods 2008
UCI eee pages
Undergrad, Human Complex Systems, UCLA

ECPR Summer School in Methods and Techniques at University of Ljubljana

Click here for the details

Instructor

Douglas R. White Evaluations Comments

Current teaching

Fall-Winter-Spring (may be taken multiple times, 1-9 quarters, 1.33 credits per quarter)

  1. Courses: Networks and Complexity (open for enrollment)
  2. Seminars: Networks and Complexity (open for enrollment); Network Theory and Social Complexity;

Fall 2007 Course 174AW Human Social Complexity and World Cultures

Fall 2008 Course 174AW Human Social Complexity and World Cultures

Fall 2008 Course 129 Breadth Kinship and Complexity

Spring Seminar Anthropological Methods and Models 2008 (taught at UCSD, UCI students by interactive video)

my courses and seminar home pages

eee pages at Irvine