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Anthropological Research

Anthropological Research. Theories, Questions, Scales, Data, and Models . Anthropological Research. Research begins with an idea or question about something: From the literature Derived from a theory or model From a discovery of a pattern in the data

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Anthropological Research

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  1. Anthropological Research Theories, Questions, Scales, Data, and Models

  2. Anthropological Research • Research begins with an idea or question about something: • From the literature • Derived from a theory or model • From a discovery of a pattern in the data • The purpose of research is to evaluate the support for that idea

  3. Theories in Anthropology • Linked sets of statements about how people behave and why, e.g. • Zipf’sLaw of the Minimum – people minimize their effort • Cultural Ecology – people behave in ways that harmonize with their environment • Behavioral Ecology – natural selection shapes our behavior

  4. Kinds of Theories in Anthropology • Biology (population genetics) • Environment/Ecology (exogenous) • Demography (endogenous) • Culture (innovation, diffusion, migration, interaction, stratification) • Psychology (individual needs/wants/ strategic action)

  5. Who Questions • Who has power? • Who has wealth? • Who is related to whom? • Who were the first agriculturalists? • Who were the first Americans/ Australians?

  6. What Questions • What do people call their kin? • What are the rules for dividing shares? • What kind of houses do they build? • What was this artifact used for? • What disturbances have altered the site?

  7. When Questions • When did the first humans emerge? • When did agriculture begin? • When did Western influences become important? • When was the New World colonized?

  8. Where Questions • Where do people live, work, play? • Where are various activities performed? • Where are people buried?

  9. Why Questions • Why do people believe in . . . ? • Why do people do . . . ? • Why was agriculture invented? • Why are pots decorated? • Why did states emerge?

  10. How Questions • How was Australia colonized? • How did the Indo European language spread? • How did human culture emerge? • How do people classify . . .? • How does globalization affect local culture?

  11. Scale • Global view – big picture processes • Temporal view – periods, phases • Regional view – social networks, territories • Local view – neighborhood • Site/Village view – structure, context • Individual view – life history, types

  12. Global View • Climate, soils, topography, ecological zones, isolation, ocean currents • Data on cultures, nations – demography, economy, ideology • Broad patterns between global characteristics and culture

  13. Temporal View • Archaeological time/space charts spanning millennia • Historical timelines spanning centuries • Generational data • Life history data

  14. Regional View • Environmental variability at regional level – rivers, mountains, vegetation, ecological communities • Locations of sites/villages • Characteristics of sites/villages

  15. Site/Village View • Site neighborhood • Location of structures, features, artifact clusters • Household composition • Variability

  16. Household View • Location (within village/site) • Pattern of structures, features, and activity areas • Comparison with other households

  17. Individual View • Physiology, genetic makeup, skeletal characteristics • Life history • Statuses and roles • Decision making • Belief system

  18. Individual (Artifact) View • Group (classification) • Composition • Properties – size, shape, color, quality, wear, breakage, material, Style vs. Function

  19. Models • A model uses a theory to develop expectations about what kinds of patterns we will find in the data • Models use theories and operational arguments to tell us what is important in the data • Statistics can help evaluate the fit between model and data

  20. Evaluation • Must check reasoning from theory to model • Must check operational arguments and proxy measures • Must check data gathering process • Must check role of formation processes

  21. Quantitative Approaches • Estimation and Confirmation • Sampling • Parametric vs. Non-parametric • Response (Dependent) vs. Explanatory (Independent) variables (causal models) • Descriptive • Data Reduction, Pattern Recognition (Exploratory Data Analysis)

  22. Kinds of Data • Scales of measurement – nominal, ordinal, interval, ratio (dichotomy) • Discrete vs. Continuous • Composition/Assemblage (Percentages)

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