Russel-Research-Method-in-Anthropology

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26 Chapter 1 those things ethically, so you can live with the consequences of your actions. I’m not exaggerating about this. Ethics is part of method in science, just as it is in medicine, business, or any other part of life. For while philosophers discuss the fine points of whether a true science of human behavior is really possible, effective social science is being done all the time, and with rather spectacular, if sometimes disturbing, success. In the mid-19th century, when Quételet and Comte were laying down the program for a science of human affairs, no one could predict the outcome of elections, or help people through crippling phobias with behavior modification, or engineer the increased consumption of a particular brand of cigarettes. We may question the wisdom of engineering cigarette purchases in the first place, but the fact remains, we can do these things, we are doing these things, and we’re getting better and better at it all the time. It hardly needs to be pointed out that the increasing effectiveness of science over the past few centuries has also given human beings the ability to cause greater environmental degradation, to spread tyranny, and even to cause the ultimate, planetary catastrophe through nuclear war. This makes a science of humanity even more important now than it has ever been before. Consider this: Marketers in a midwestern city, using the latest supercomputers, found that if someone bought disposable diapers at 5 p.m., the next thing he or she was likely to buy was a six-pack of beer. So they set up a display of chips next to the disposable diapers and increased snack sales by 17% (Wilke 1992). At the time, 15 years ago, that was a breakthrough in the monitoring of consumer behavior. Today, every time you buy something on the Internet or download a computer program or a piece of music, you leave a trail of information about yourself and your consumer preferences. By tracking your purchases over time, and by sharing information about your buying behavior across websites, market researchers develop ads that are targeted just for you. We need to turn our skills in the production of such effective knowledge to solving the problems of hunger, disease, poverty, war, environmental pollution, family and ethnic violence, and racism, among others. Social scientists, including anthropologists, can play an important role in social change by predicting the consequences of ethically mandated programs and by refuting false notions (such as various forms of racism) that are inherent in most popular ethical systems. This has been a hallmark of anthropology since Franz Boas’s devastating critique, nearly a century ago, of racial theories about why some ethnic minorities in the United States were taller and healthier than others. Don’t get me wrong here. The people who discovered that fact about the six packs and the diapers were good scientists, as are the people who design all those automated data-collection mechanisms for monitoring your behavior on the Internet. I’m not calling for rules to make all those scientists work on
Anthropology and the Social Sciences 27 problems that I think are important. Scientists choose to study the things that industry and government pay for, and those things change from country to country and from time to time in the same country. Science has to earn its support by producing useful knowledge. What ‘‘useful’’ means, however, changes from time to time even in the same society, depending on all sorts of historical circumstances. Suppose we agreed that ‘‘useful’’ means to save lives. AIDS is a terrible disease, but three times as many people died in motor vehicle accidents in 2002 as died of AIDS (about 44,000 and 14,000 respectively). Should we spend three times more money teaching safe driving than we do teaching safe sex? I think the answer is pretty clear. In a democracy, researchers and activists want the freedom to put their skills and energies to work on what they think is important. Fortunately, that’s just how it is, and, personally, I hope it stays just that way.
Page 1: H. Russell Bernard FOURTH EDITION R
Page 5 and 6: Research Methods in Anthropology Fo
Page 7 and 8: Contents Preface vii 1. Anthropolog
Page 9 and 10: Preface Since 1988, when I wrote th
Page 11 and 12: Preface ix sampling: why we do it a
Page 13 and 14: Preface xi 21, you will be able to
Page 15 and 16: Preface xiii testimony. There is an
Page 17 and 18: Preface xv begin writing the second
Page 19 and 20: 1 ◆ Anthropology and the Social S
Page 21 and 22: Anthropology and the Social Science
Page 43: Anthropology and the Social Science
Page 47 and 48: The Foundations of Social Research
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Page 89 and 90: Preparing for Research 71 research
Page 91 and 92: Preparing for Research 73 morning u
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Preparing for Research 77 showed wh
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Preparing for Research 79 That will
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Preparing for Research 81 mothers.
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Preparing for Research 83 gathering
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Preparing for Research 85 hypothesi
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Preparing for Research 87 I mention
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Preparing for Research 89 A Guide t
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Preparing for Research 91 people re
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Preparing for Research 93 Observed
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Preparing for Research 95 dent. (Re
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The Literature Search 97 too busy t
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The Literature Search 99 year, who
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The Literature Search 101 like demo
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The Literature Search 103 reports e
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The Literature Search 105 gists, in
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The Literature Search 107 Women Sca
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5 ◆ Research Design: Experiments
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Research Design: Experiments and Ex
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Sampling 147 ried around here deliv
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Sampling 149 the potential sampling
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Sampling 151 they’re joined by al
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Sampling 153 116. If the first rand
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Sampling 155 off base in our thinki
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Sampling 157 Cluster Sampling and C
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Sampling 159 Probability Proportion
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Sampling 161 you will properly surv
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Sampling 163 the cluster, the large
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Sampling 165 TABLE 6.2 Comparison o
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Sampling 167 25 Number of Household
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7 ◆ Sampling Theory Distributions
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Sampling Theory 171 In normal distr
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Sampling Theory 173 a lot of inform
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Sampling Theory 175 TABLE 7.2 All S
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Sampling Theory 177 12 10 Number of
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Sampling Theory 179 Calculating Sam
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Sampling Theory 181 Look up what’
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Sampling Theory 183 and we solve fo
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Sampling Theory 185 ables combine t
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Nonprobability Sampling and Choosin
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TABLE 8.4 Matches, Proportions of M
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Interviewing: Unstructured and Semi
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10 ◆ Structured Interviewing I: Q
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Structured Interviewing I: Question
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11 ◆ Structured Interviewing II:
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Structured Interviewing II: Cultura
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Scales and Scaling 319 10 times, or
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Scales and Scaling 321 students’
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Scales and Scaling 323 points. The
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Scales and Scaling 325 TABLE 12.2a
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Scales and Scaling 327 wealth in vi
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Scales and Scaling 329 You may obse
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Scales and Scaling 331 interitem co
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Scales and Scaling 333 ality of a s
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Scales and Scaling 335 TABLE 12.7 T
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Scales and Scaling 337 Having a Col
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Scales and Scaling 339 The Cantril
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Scales and Scaling 341 and has been
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Participant Observation 343 Romanci
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Participant Observation 345 sion, s
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Participant Observation 347 doses o
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Participant Observation 349 great s
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Participant Observation 351 less—
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Participant Observation 353 oped by
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Participant Observation 355 Graham
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Participant Observation 357 ters fr
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Participant Observation 359 washing
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Participant Observation 361 that yo
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Participant Observation 363 ‘‘c
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Participant Observation 365 hall wh
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Participant Observation 367 Maintai
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Participant Observation 369 not to
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Participant Observation 371 pletely
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Participant Observation 373 changed
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Participant Observation 375 Besides
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Participant Observation 377 Thomas
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Participant Observation 379 But not
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Participant Observation 381 baby’
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Participant Observation 383 into fo
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Participant Observation 385 in Mace
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14 ◆ Field Notes: How to Take The
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Field Notes: How to Take Them, Code
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15 ◆ Direct and Indirect Observat
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Direct and Indirect Observation 415
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16 ◆ Introduction to Qualitative
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Introduction to Qualitative and Qua
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START: SEARCH WHOLESALE MARKET FOR
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17 ◆ Qualitative Data Analysis I:
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Qualitative Data Analysis I: Text A
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19 ◆ Univariate Analysis The next
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Univariate Analysis 551 But if you
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Univariate Analysis 553 TABLE 19.1
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Univariate Analysis 555 Notice in t
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Univariate Analysis 559 TABLE 19.3b
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Univariate Analysis 561 possible an
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Univariate Analysis 563 people hang
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Univariate Analysis 573 Number of C
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Univariate Analysis 575 some basic
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Univariate Analysis 577 interquarti
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Univariate Analysis 579 countries t
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Univariate Analysis 581 Both groups
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Univariate Analysis 585 would be no
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Univariate Analysis 587 rejecting H
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Univariate Analysis 589 lation, 68.
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Univariate Analysis 591 of Shipibo
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TABLE 19.13 Chi-Square for a Univar
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Bivariate Analysis: Testing Relatio
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TABLE 20.20 Correlation Matrix of A
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21 ◆ Multivariate Analysis Most o
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Multivariate Analysis 651 environme
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Multivariate Analysis 653 TABLE 21.
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TABLE 21.11 Wealth by Education, Co
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Multivariate Analysis 657 it is hig
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Multivariate Analysis 659 ideas abo
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Multivariate Analysis 661 You can a
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Multivariate Analysis 663 which mea
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Multivariate Analysis 667 In fact,
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Multivariate Analysis 669 under plo
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Multivariate Analysis 671 fr .968 R
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Multivariate Analysis 673 earity pr
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Multivariate Analysis 675 BTU and O
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Multivariate Analysis 677 Factor An
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Multivariate Analysis 679 columns h
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Multivariate Analysis 681 4. Across
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Multivariate Analysis 683 instead o
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Multivariate Analysis 687 1.71 1.32
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Multivariate Analysis 689 ‘‘chi
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Multivariate Analysis 691 6, 1, 4.
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Multivariate Analysis 693 Lambros C
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Multivariate Analysis 695 just beca
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698 Appendix A 32179 00597 87379 25
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APPENDIX B Table of Areas under a N
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702 Appendix B (A) (B) (C) (A) (B)
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APPENDIX D Chi-Square Distribution
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APPENDIX E F Table for the .05 Leve
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708 Appendix E F Table for the .01
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APPENDIX F Resources for Fieldworke
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712 References obesity in Saudi Ara
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714 References Beautrais, A. L., P.
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716 References the self-assessment
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718 References Bradburn, N. M. 1983
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720 References ments by considering
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722 References ing in reflected glo
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724 References village. In Self, se
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726 References Duncan, O. D. 1966.
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728 References achieve high respons
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730 References Gatz, M., and M. Hur
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732 References C2KBR/01-1. Washingt
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734 References study of relationshi
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736 References Hornik, J., and S. E
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738 References esses in survey rese
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740 References Kessler, R. C., and
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742 References Laban Moogi Gwako, E
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744 References Lewis, R. B. 2004. N
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746 References McCall, G. 1978. Obs
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748 References Morgan, D. L. 1997.
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750 References Oakhill, J., and A.
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752 References Piliavin, I. M., J.
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754 References nicity-of-interviewe
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756 References Rotton, J., and M. S
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758 References Schwarts, N. A. 2004
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760 References Smith, L. D. 1986. B
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762 References Stricker, L. J. 1988
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764 References pharmacists in HIV/S
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766 References Webb, E. J., D. T. C
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768 References Williams, T. 1996. E
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Subject Index Numbers in italics re
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Subject Index 773 Campos, Alberto,
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Subject Index 775 data analysis, 45
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Subject Index 777 external states,
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Subject Index 779 individual attrib
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Subject Index 781 median, 562, 563-
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Subject Index 783 parsimony, princi
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Subject Index 785 random digit dial
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Subject Index 787 simple scales, 31
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Subject Index 789 T-scores, 591 t-t
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Author Index Numbers in italics ref
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Author Index 793 Choi, N., 33 Choms
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Author Index 795 Gregson, S., 93 Gr
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Author Index 797 Leap, W., 376 LeCo
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Author Index 799 Rashid, R. G., 121
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Author Index 801 Vadez, V., 55, 93
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