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The Dual Ordering of Actors and Possessions

Author(s): Thomas SchweizerSource: Current Anthropology, Vol. 34, No. 4 (Aug. - Oct., 1993), pp. 469-483Published by: The University of Chicago Presson behalf of Wenner-Gren Foundation for AnthropologicalResearch

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Volume 34,Number4, August-October 1993 | 469MC CORRISTON, J., AND F. HOLE. I99I. The ecology f ea-sonalstiess nd theorigin f griculturen theNear East.American Anthropologist93:46-69.MILLER, N. I99I. "Archaeobotanicalesearchn the Near East,"in Progressn Old World alaeoethnobotany.dited yW. vanZeist,K.Wasylkikowa,nd K.-E.Behre, p. 33-60. Rotter-dam: Balkema.

. i992. "The origins fplant ultivationn theNear East,"in Theorigins f griculturen internationalerspective.d-itedby C. W.Cowanand P. J.Watson, p.39-58.Washington,D.C.: Smithsoniannstitution ress.MOORE, A. M. T. I985. The developmentfNeolithic ocietiesin theNear East.Advances n WorldArchaeology: I-70.MOORE, A. M. T., AND G. C. HILLMAN. i992. The Pleistoceneto Holocene ransitionndhuman conomyn SouthwestAsia:The impact f theYounger ryas.AmericanAntiquity57:482-94.NAHEV, Z., AND R. H. WHITTAKER. I979. Structuralnd flo-ristic iversityf hrublandsndwoodlandsn northernsraeland otherMediterraneanreas.Vegetatio 4I:I7I-90.NIKLEWSKI, J., AND W. VAN ZEIST. I970. A lateQuatemarypollendiagram rom orthwestemyria.Acta BotanicaNeer-landica 9:737-54.ROBERTS, N., AND H. E. WRIGHT, JR. I993. "The Near Eastand outhwestAsia," in Global climatic changes since the astglacial maximum. dited yH. E. Wright, r., . . Kutzbach,T. Webb II,W. F.Ruddiman,. A. Street-Perrott,nd P. J.Bartlein.Minneapolis: niversityfMinnesota ress.STREET-PERROTT, F. A., AND A. PERROTT. I993. "Holocenevegetation,ake evels, ndclimate fAfrica,"nGlobalclimates ince the astglacialmaximum. dited yH. W.Wright, r., .E. Kutzbach, . Webb II,W.F.Ruddiman,. A.Street-Perrott,ndP. J.Bartlein.Minneapolis:UniversityfMinnesota ress.VAN ZEIST, W., AND S. BOTTEMA. I977. Palynologicalnvesti-gationsnwesternran.Palaeohistoria9:I9-85.. I99I. LateQuatemary egetationn theNear East.BeihefteumTiibinger tlas des Vorderen rients, (Natur-wissenschaften),8.VAN ZEIST, W., S. BOTTEMA, H. WOLDRING, AND D. STA-PERT. I975. Late Quatemary vegetationand climate ofsouth-eastern urkey. alaeohistoria7:53-I43.VAN ZEIST, AND W., AND H. E. WRIGHT, JR. I963. Prelimi-nary ollen tudies t LakeZeribar, agrosMountains,outh-western ran. Science I40:65-67.

WATSON, P. J. 99I. "Origins offoodproduction n westemAsiaand easternNorthAmerica,"n Quaternaryandscapes.Edited yL. C. K. Shane nd E. J.Cushing, p. -37. Minneap-olis:UniversityfMinnesota ress.WIJMSTRA, T. A. I969. Palynologyfthe first0 meters of aI3o-m-deepectionnnorthem reece.Acta BotanicaNeerlan-dica I8:5II-27.WRIGHT, H. E., JR. I960. "Climate ndprehistoric an n theeasternMediterranean," n Prehistoric nvestigations n IraqiKurdistan. dited yR.J.Braidwood ndB.Howe,pp.7I-97.Chicago:Orientalnstitute, niversityfChicago.. I96I. Pleistocene laciationnKurdistan. iszeitalterundGegenwart12:I3i-64.. I968. Natural nvironmentfearly oodproductionntheNear East.Science 6I:334-39.. I976. Environmentalettingor lantdomesticationntheNear East.Science 94:385-89.. I984. "Palaeoecology,limatic hange, nd Aegean rehis-tory,"n ContributionsoAegeanarchaeology: tudies nhonor fWilliamA. McDonald.Edited yN. C. Wilkie ndW.D. E. Coulson,pp. 83-95. Dubuque:Kendall/Hunt.. I989. The amphi-AtlanticistributionftheYoungerDryas limatic luctuation.uaternary cienceReviews8:295-306.WRIGHT, H. E., JR., J. H. MC ANDREWS, AND W. VAN ZEIST.1967. Modern ollenrain nwestern ran nd ts relation oplantgeographyndQuatemary egetation istory. ournalfEcology 5:4I 5-43.

The Dual Orderingof Actorsand Possessions1THOMAS SCHWEIZERInstitut ir Volkerkunde,University f Cologne,Albertus-Magnus-Platz,W-5oooK5ln 4I, Germany.6 IV 93Although nthropological ieldworks oftenconceivedas a "qualitative"undertaking,s a matter f fact eth-nographers atherconsiderablenumericalinformationin the course ofcensuses, surveys, nd systematic b-servations n theirfield sites (Bernard988). Typicallythesedata sets coverratherarge ets of units individu-als, households, etc.) in termsof qualitative conceptsspecifyinghepresence/absence fattributes,member-ship n a system fcategories, r therankorder fsuchcategories. xamplesare data on theoccurrence/nonoc-currence fmaterialpossessions,classifications f resi-dence,religious ffiliation, ccupation, nd social class,and observations n the amounts of powerand socialstatus which actorspossess within a social system. nthe languageofformaldata analysis (Gifi 990) thesevariablesare called categorialor discrete.The empiri-cal relationships hey express can be formally epre-sented as nominal scales (stating hepresence/absenceofa propertyrmembershipn a systemofcategories)or ordinal cales (conceptualizing heamount ofa prop-erty). ne can countandcompare hefrequencies fthevalues ofdiscretevariables,but the categories re notdivisible s arecontinuousvariablesmeasuredon inter-val or ratioscales (where, s, for xample,with mone-tary ncome, the exact difference etween numericalvalues has empirical meaning). Continuous variablesare,however, eryrare n social research.Observationaldata are usually arrangedn the formofa rectangular x m matrix fn units ofobservation(rows) nd m variables columns), nd the values of thevariablesare coded numerically.An arbitrarylementof this data matrix pecifiesthe value ofvariable forunit . Social researchers ftenhave recourse o tabularanalysisoftwo ormorevariables, weak procedure ordetecting he structure f relationships mong all thevariablesf he et Gifi990:43-46). Inprinciple ulti-variate nalysisofthe whole data matrix-"the analysisof n arbitraryectangularmatrix,with theexplicitpur-poseofdescribinghematrix n terms f smallernum-ber of parameters nd of making pictures of this re-I. This apers an outcomef joint rojectndiscretetructureanalysisnvolvingocialscientists romheUniversityfCalifor-nia, rvine, RNS (Paris), nd theUniversityfCologne.An earlierversion aspresentedt a conferencendiscretetructuresnthesocial sciences t theMaisonSugern Paris n September992. IthankVincent uquenne,Douglas R. White,Hartmut ang,Mi-chaelBollig, hristoph rumann, parnaRao,participantsntheconference,nd anonymous efereesor his oumal fordetailedand helpful omments. uquenne's (i992a) formal upport ndcomputationalork n theJavaneseataset were nvaluable.

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470 1CURRENT ANTHROPOLOGY

presentation" Gifi I990:49)-provides a better dataanalytic olution. t has, however, raditionallyocusedalmost exclusively n continuousvariables nd statisti-calmodels appropriate or heanalysisofmultinormallydistributedariables Gifi 990:43), and thisorientationhas imposedsevere restrictionsn data analysis.Modelassumptionshave rarelybeen met by empiricalsocialresearch. Furthermore, iscrete variables have beentreated s special cases of continuousvariables, nd nospecialconsideration as beengivento problems fdis-cretedata analysis see,however,Bishop,Fienberg, ndHolland I97-5). Recently he situationhas changed ub-stantially: rom pplied statisticshas emerged henew(sub)discipline f data analysis, hallenging ndrethink-ing old assumptions, models, and techniques (Gifii990:chap. i). Gifi i990:52) arguesthat "all data arediscrete or categorial),"continuous models being ap-plied to them"to simplify alculationsand approxima-tions,"and that t may even be appropriate o convertobservationsn continuousvariables o discrete ataforthe purposeof better ecovery fthepattern f relation-shipsamongthem pp. 2I-32).Another ecent urrentn social sciencedataanalysisis theexploration fmethodsfrom et theory, raph he-ory,algebra, nd formal ogic (as branchesof discretemathematics)forrepresentingtructural elationshipsamongcategorialdata (see White and Duquenne I993for n overview).The focus on qualitativedata and theconcernwith structure remostappealing o anthropol-ogy; recourseto well-established oncepts and proce-duresfrom iscretemathematics ddsformal recision,methodological igour,nd analytic lexibilityacking nearlier nthropologicaltructuralisms.n addition, hereare now computerprograms hat make data analysispractical see, e.g.,Duquenne I992b; White 99I; De-genne and Lebeaux i992). So far, nthropological ndsocial scienceapplicationsof discrete tructure nalysishave includedgraph nalysisofkinship, xchange, ndsymbolic rderingsHage and Harary 983, I 99 I; WhiteandJorion992), latticeand statistical ntailment nal-ysisof social network nd cognitivedata (Freeman ndWhite i992, White and McCann I988, White et al.I993), and Boolean dissectionof causal patterns De-genne i992; Lang I993a, b; Schweizer I993a). In a sensethismovement ursuestheconcerns folder tructural-isms n the social sciences,buttoday's tructuralnaly-sis examines orderingsn empiricaldata with precisemethodsand computerprograms nd thus avoids theflawsof tspredecessors.After long periodofneglect,materialculturehasrecently eceivedrenewed attention Appadurai 986;Featherstone 99I; Ferguson 988, I992; McCrackenI989; Miller 987; RutzandOrlove 989; Sahlins 988;Thomas i99I; for forerunnersee Douglas and Isher-wood I978, Bourdieu 979). Current esearch ocusesonthe culturalconstitution fthings, he symbolicvalueofgoods,theproduction-exchange-consumptionexus,the expressionof social distinctions n particular ife-styles, nd thewayinwhich theembeddedness f com-munities n larger, venglobalnetworks f communica-

tion, roduction,nd exchange ffectshe cultural se ofthings t thelocal level. New theoretical nd empiricalquestionshave been posed, and a richerunderstandingof materialculture has been gained. There has been,however,no correspondingmprovementn systematicmethodsfor assessing ethnographic ata on materialculture.n this paper shall explore he prospects f onediscretemethod, atticeanalysis,for he elucidationofthe ordering f actors and possessions in materialpos-sessions data.Ethnographicand comparative research producesmanydata setswhich simply pecify or set of actors(persons, ouseholds)which temsfrom list of posses-sionsconsidered elevant n the communitytudied representor absent (Castro,Hakansson, and BrokenshaI98I). Oftenthis informations displayed n a table ofactors rows) nd possessions columns).2n data analy-sis manyresearchers estrict heir ttention o univari-ate frequencies fparticular ossessions or to the pro-files of specific actors, present valuable and partialbackgroundnformationn themeaning, alue,anduseof elected tems,or compute sometimes rude) ndicesofmaterialwealth. However,there s more to these bi-narydatamatrices han this, ndrarelyfever arethesedata analyzed n a sophisticated ndcomprehensive ay(Kay I964 is an early exception).The discretemethodthat propose or ata analysiscan be appliedto materialpossessionsdata of this canonical form n an attemptto recover he ordering attern mongactorsand pos-sessions systematically Schweizer I993b; Duquennei992a, b).The dual ordering roblem nherentn materialpos-sessionsdata can be introducedwithBourdieu's I979)influential and controversial see Elster 98I]) studyofsocial class and life-stylesn contemporaryrench oci-ety.Bourdieu analyzes the symbolicand social valuesassociated with particular possessions-the way inwhich classes and class fractions eproduce hemselvesby paying lose attention o life-stylesnd engagingnever-shiftingompetitive onsumptivedisplays.He hy-pothesises a mappingbetween social actors (that is,classes or class fractions) nd particularpatternsofconsumption and uses the statistical technique ofcorrespondencenalysis (Wellerand Romney iggo) torepresent t in a common geometric space of lowdimensionality. his leads to thenotion ofdual order-ing: an orderingmong possessions,giventheirparticu-lar distribution mong the set of actors,an orderingamong ctors, enerated ytheirprofiles fpossessions,2. Formally,ossessions-by-actoratricese.g., he table n Ichi-kawa I99I:I42-43) can be treatedthe same way by transposingthe matrix nd thus nterchangingows and columns.A valueddatamatrix n thefrequenciesf possessions an easilybe trans-formednto binary ata matrixseealso Gifi 990: chap. ). Con-ceptually distinctionasto be madebetween nits f bservation(actors,bjects) nd variables attributes,tems, ossessions)mea-sured or he unitsofobservation.n explaininghe atticemodelI shall use the general bject/attributeistinction,nd in an ap-pliedmaterial ossessionsontext shallrefermore pecificallyoactors/possessionsr actors/items.



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Volume 34, Number 4, August-October '993 | 47I

and the interlocking attern onnecting he two. Thisnotion, houghnot alien toBourdieu'swork, s notfullydeveloped thereor conceptualized precisely.However,whateverone's substantive nd theoretical nterpreta-tions of such data on materialculture, epresentinghedual ordering f actorsand possessionsin a preciseandsystematic way is fundamental.Lattice analysis hassome important rospects or histask: it staysclose tothe observationaldata and is well suited to dissectingthe overall ordering tructure nd the in-depth atternof objects/attributesn binarydata matrices.Buildingon earlierwork Duquenne i992b, SchweizerI993b), Ishall trace dual ordering tructures mong actors andpossessionswith this discrete method.The focuswillbe on ethnographic ata setsfrom ifferentultures, l-lustratinghepotentialof atticeanalysisfor ompara-tivestudies.CASE STUDIES OF ELEMENTARY ORDERING PATTERNSA well-knownmaterial possessions data set collectedby Kay i964) in Papeete,FrenchPolynesia,records hedistributionof seven consumer durables among 40households n this Tahitian town table ). Kay detectedan interlocking ual ordering attern ndrepresentedtin a Guttman scale, ranking he householdsaccordingto the frequency f theirpossessions and the durablesaccording o their ointoccurrence.n thisranking,fahoushold possesses a certain tem, t will also possessall the items orderedbelow that item; if a householddoes not possess a particular tem, t will not possessanyof the temsabove that tem n theorder. f suchanorderings possibleempirically,hen actors ndposses-sions canbe representedna Guttman cale. Thus Gutt-man scaling ooksfor maximally ransitive nd consis-tentrepresentationf therows and the columns of thedata matrix.However,theGuttmanmodel-a sophisti-catedtoolofdata analysisat thattime-imposes a uni-dimensional rderingn the nputdata.Formostempir-ical datasetsandforarge ets of temsthis trict atternwill be rather nlikely and at best onlyapproximated.Hence a moregeneralsolutionshould allow for lessrestrictivemultidimensional) epresentation f dual or-dering tructures.n a recent ntroduction ocorrespon-dence nalysisWeller nd RomneyI990:79-83) reana-lyzetheKaydata andrepresentt in a two-dimensionalgeometric pace. Figure is a simplified ersionoftheresultsof correspondence nalysis depicting he com-mon presences among the set of durables (computedwith the UCINET IV program uite for ocial networkanalysis Borgatti, verett, nd Freeman 992]; in theirmorecomprehensive nalysis Weller and Romneyalsoinclude the nonoccurrenceof items). The closer twoitems are in geometric pace, the more frequent s theirjoint occurrence n the set of households. In this casethesuccessiveorderingfthe tems n space (from ightto left)reflects he orderof their acquisition and theirvalue.This sequence leads from rimus tove and bicy-cle as widely shared consumer items of low valuethrough adioand two-wheeledmotorvehicle and then

TABLE IPresence i) or Absence (o) of Seven Consumer Goodsfor 0 Households in Papeete (afterKay I964:I6I-62)House- House-hold holdA F K V R B P Number A F K V R B P Number

I I I I I I I I 0 0 0 0 I I I 2II I I I I I I 2 00 0 0 I I I 220 I I I I I I 3 0 0 I 0 0 I I 230 I I I I I I 4 0 0 0 I 0 I I 240 I I I I I I 5 0 0 0 0 0 I I 250 I I 0 I I I 6 0 0 0 0 0 I I 260 I I 0 I I I 7 0 0 0 0 0 I I 270 0 I I I I I 8 0 0 0 0 0 I I 280 0 I I I I I 9 0 0 0 0 0 I I 290 0 I 0 I I I IO 00 0 0 0 I I 300 I 0 I I I I II 0 0 0 0 0 I I 3I0 I 0 I I I I I2 00 0 0 0 I I 320 0 0 I I I I I3 0 0 0 0 0 I 0 330 0 0 I I I I I4 0 0 0 0 0 0 I 340 0 0 I I I I I5 0 0 0 0 0 0 I 350 0 0 I I I I i6 0 0 0 0 0 0 I 360 0 0 0 I I I I7 0 0 0 0 0 0 I 370 0 0 0 I I I I8 0 0 0 0 0 0 I 380 0 0 0 I I I I9 0 0 0 0 0 0 I 390 0 0 0 I I I 20 00 0 0 0 0 0 40NOTE: A, automobile; , bicycle;F,refrigerator;, kerosene rgas stove;P,primus tove;R, radio;V,two-wheeled otor e-hicle.keroseneorgas stoveand refrigeratoro automobile asa rare ndhighly alued luxury tem.Householdscouldbe placedin thosepartsof thespace which fit heirpar-ticular arraysof durables-for example, poorer onesclose to theprimus tove, ichonesneartheautomobile,and middle-class nes in between.Given the usefulgeometric epresentatione.g.,fig. )and thedata reduction apacityofstandardmethodsofstatisticaldata dredging,what additional analytic in-sight anbe gainedby applying iscretemethods o ma-terialpossessionsdata?One should note nitially hat ttheroot ofall materialpossessions examplesare ogicalimplications, f-then elations specifying oint occur-rences among the items of the set. These relationsamongitems lead to a discreteordering f actors.Forinstance, fan actorpossesses itemA, then does he/shealso possess items B and C, etc.? Logical implicationsare the basis of lattice analysis (Duquenne igg2a, b;Freeman nd White 992; Wille I990), and thereforetis natural o represent inarymaterialpossessions dataina lattice.Lattice nalysisextracts ll the ogical mpli-cationsamongthe items of the set and represents heorder enerated mongactorsofthe setbytheirparticu-larcombinations fpossessions. This interlocking rderis faithfullynd comprehensively omputed fromtheraw data.Latticeanalysis s bestconceived as a methodofdual scalingwhich ooks for trict mplications n thedata andrepresentshenestedorderingf ttributes ndobjects = actors,units ofobservation). he dual order-



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4.54AUTO

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1.99KEROSENE0.71 - PRIMREFRIG

BICYCLE-0.56 - RADIOVEHICLE-2.54 -1.76 -0.97 -0.18 0.60

FIG. i. Optimal scaling of consumerdurables automobile,refrigerator,erosene orgas stove, two-wheeledmotorvehicle,radio, bicycle,primus stove) n 40 Papeetehouseholds.ing pattern an be visualized in the form f a line dia-gram. Thus lattice analysis yields precise informationon the totalpattern f ogical implications ontained nthe dataand represents he exactdualordering tructureofactors ndpossessions n termsof mplications.Latticeanalysiscan be applied to any binary ata ma-trix.Fordata analysis use the GLAD (General LatticeAnalysis and Designs) programdeveloped by VincentDuquenne (igg2b).3At present heprogram an handleup to 32 attributes. he data are input as a raw binarydatamatrix uch as thatoftable . Within he programa preprocessing f the data is executed by extractingrowsand columns which are duplicatesor compositesof attributes nd objects retained n the reduced dataset.This loss of tructurallynimportantnformationsdocumented,ndthe ost information an be recovered;when the user demandsfrequencies utput, ll the dataare included. n a routine pplication ofGLAD, the re-duced data set is analyzed, and two images are drawn:an image of thepartialorder f attributes nd an imageof he atticedepicting ll implications mong ttributesand the nestedordering fobjects.The list of mplica-tionsproducedbytheprograms fundamental or om-puting nd drawing he images.The total set of mplications or heKaydata s shownin table2. The firstmplication, or nstance, s, that fa household owns an automobile A), then t also pos-sesses a refrigeratorF), a kerosene or gas stove (K), atwo-wheeledmotorvehicle V),a radio R),a bicycle B),and a primus tove P). This situation s thecase in 2 of

the40 households.Therewill be no household with anautomobilewhichdoesnot also possess all the ndicateditems (readers an check this claim by inspecting heraw data in table I). A single occurrence fan automo-bile without nyoftheother temswould havefalsifiedthis implication. n lattice analysis exceptionsto thestrict mplicativerules are not allowed (but see belowon relaxation f thiscondition).Empirically n theKaydata,all implications xceptthe last one containprem-ises withone elementonly, hat s, one attributen theif-componentf the hypothesis.The last one containsa multiple-element remise.These elements are con-nectedbya logicalconjunction only fall conditions nthepremise re true can we expectthe outcome n theconclusion): f household ownsa kerosene rgas stove(K),a two-wheeledmotorvehicle (V), a bicycle B), anda primus tove P),then t also owns a radio R).This isthe case in 7 households ofthesample.The twoimagesTABLE 2Implications mong ConsumerDurables and NumberofCases Fulfilling ach in PapeetePremise Conclusion Number f CasesA FKVRBP 2F RBP 9K BP IIV BP I4R BP 22KVBP R 7NOTE: A, automobile; , bicycle: ,refrigerator;, kerosene rgas stove;P,primus tove;R,radio; V, two-wheeled otor e-hicle.

3. GLAD is a shareware rogramhat anbe ordered rom . Du-quenne, IO bis, rue A. Payen, F-750I5 Paris, France. A single-userpersonal license costs $ioo. Other programsforlattice analysis(e.g., Burmeister 99I, Vogt nd Bliesener99i) are available fromthe Department of Mathematics, Technical University ofDarm-stadt, Schlossgartenstrasse , D-6 oo Darmstadt, Germany.



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Volume34, Number4, August-October 993 1473mentioned bove use the information n implicationsin thedata set in different ays.The image of thepartial orderof attributes ocusesexclusively n implicationswith single-element rem-ises. Very ften, owever, hegistofthe mplications fa data set is alreadycapturedbythese implications; nthe Kay data set this is clearlythe case. Therefore hevisualizationofthepartialorder f attributes an be un-derstood s a roughview of the structure fattributes.Frequent nd commonattributeswill be placedtowardsthe top,more pecific nd rareones towards he bottom.The top node is empty (conceptualizingthe case inwhichall attributesrenonoccurring). oving upwardsalong the lines or arrowsconnecting ttributes racesthe implicationalordering mongthe attributes f thesetbased on single-elementmplications.The line dia-gramsof attice analysis in contrast o geometric lotsfrom ontinuous multivariate nalysis, e.g.,Gifi 990,Weller ndRomney 990) havenometric;onlythe rela-tivepositions fpointsconnected y inesare mportant.The line diagram ofthe attice includesall attributesand objects from he reduced dataset) and all implica-tions.This image s certainlymore nformative ut alsomorecomplicated han the mageof thepartialorder fattributes.Generally t represents he dual ordering fattributes nd objects n such a way thatthetopof thelatticedepictsthe union of all objects and the bottomtheunionof all attributes. bjects areplacedundertheattributes hichthey ossess. Ascendingines show og-ical implications; long these ines all of the ogical m-plications between attributes nd the particularcom-bination of attributespossessed by an object can berecovered. ttributesppearingnupperpartsofthe at-tice are moregeneral ndfrequent,hose n lowerpartsmore specific and restricted n their distribution. b-jectstowards hetop possess fewer ttributes han thosein the lowerparts of the lattice (hence objects whichpossessnone oftheattributes repushedto thetop,andtherewill be no objectat the bottomnodewhen no onepossesses all attributes). ollowingthe lines,hierarchi-cal orderings mongthe attributes nd amongthe ob-jects can be recovered.Given the faithful ne-to-onemappingof the (reduced)data matrix nto the lattice,one can reconstruct oreach object its exact profile fattributes. hus data and theirvisual representationnthe lattice are closely related and can be cross-checkedto increaseunderstanding.

Withmanyattributes nd abundant variation n thedatasetthepattern nd consequently he ine diagramswill be complex. Reducing the data set by eliminatingsuperfluousnformations a firstteptowards he reduc-tionof omplexity.n addition, artial nd more bstractviews of the latticeare availablewithin attice analysisas aids to patternrecognition orcomplicated data. Afurtherevelopmentn latticeanalysis s the inclusionofstatisticalprocedures. n thepreprocessing tage sta-tistical entailmentanalysis (White 99i) can be usedto eliminaterandomvariation n the data. When thetransformedata are input nto the attice program, heassumption fstrict mplications s thereby elaxed see

Schweizer 993b). The use andmastery f comprehen-sive lattice analysis program such as GLAD requiresome time and experience.The program utomaticallydraws inediagrams fthepartialorder f ttributes ndthe attice.Afternspection ndwithsome skillthe m-agescan often e optimizedwithin heprogram ymov-ing points to enhance the clarity f the drawings.This"art" componentof attice analysisdoes not affect hestructuralnformation n a data set (including he fun-damentalcomputations nd images); this informationwill always be the same forany user of the program.Rather, t is a matter of refining he diagramswithinthe limits of the implicationalorder.Pictures becomeclearerwhen fewer ines intersect, nd more parallellines arecreatedby movingpoints accordingly. or datasets that arewell structured ndnot too large, hecom-puter-producedmages themselves are rather nforma-tive. Forexample, figures and 3 are takenright romtheprogram,ndfigures and 5 areslightly edrawn utwere alreadyrevealingas machine-produced. reakingdown complex data sets calls formore experience ndtechnical ssistance. Thereare,however, cceptable n-termediate esults, nd the structuralnformations al-waysthere lbeitmoreor ess clouded. After ll,visual-izationofpatternn empiricaldata is an importantaskin itself and often an essential part of data analysis(Tufte I983; Klovdahl 98I; Gifi 990:60-6I, chaps. 3,I 3).Figure is an image of the partial order f attributesand hence of ll implicationswithsingle-element rem-ises (depicted y arrows) n the Tahitiansample. n con-trast to the geometricplot of figure , the nonspatiallattice mageincludesthe exact implicationalrelation-ships (based on single-elementpremises) among theitems. Following the arrows, presence of an item atthe bottom of the lattice implies presenceof items atthe top. The items are orderedby generality rom op(common tems such as primus stove and bicycle) tobottom restrictedtems such as automobileand refrig-erator).Furthermore, e can exactly specifydifferentimplicationalpaths.For nstance,refrigerators associ-atedonlywithradio,bicycle, nd primus tove,notwithkerosene or gas stove or two-wheeledmotor vehicle.Keroseneorgas stove,two-wheeledmotorvehicle, andradio are structurally quivalent in thatthey have thesame consequences.Figure3, based on the reduceddata set oftable 3, isan imageofthe lattice and thusgives a completeviewof thepossessionspatternn theTahitian case-all im-plications mong tems, ncluding hose withmultiple-elementpremises, reshown, ndtheorderingfhouse-holds s depicted s well. (Forthesedata this point doesnot makemuchdifference,ecause all butone implica-tion are based on single-element remises.)Householdsaredepictedundertheirparticular ombinations fpos-sessions.Whenthere reseveralhouseholdswith denti-cal patterns, nlyone case is represented see table 3),buthistogram ars in the diagram how the frequencyofeach combination n the completeraw data. The setof households is partitioned nto wealth classes ac-



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474 CURRENT ANTHROPOLOGY

B

FIG. 2. Thepartial orderof consumerdurables nPapeete. A, automobile; B, bicycle;F, refrigerator;,keroseneorgas stove; P, primus stove; R,radio; V,two-wheeledmotorvehicle; I, absence ofall items.cording o theirparticular ombinations f possessions.A wealthgradient an be grasped eadingfrom herich-est households at the bottom throughmiddle-classhouseholds n between to thepooresthouseholdsat thetop.Thus in one condensed mage attice nalysisyieldsa comprehensive,recise, ndparsimonious epresenta-tion of the dual ordering f actors and possessions inthis stratifiedociety.The Tahitian data weregatherednan urbanneighbor-hood of a stratifiedociety.What does a lattice of ma-terialpossessions data look like in a more egalitariansociety,mainlybased on the division of labor by ageand sex? This questionwill be answeredby turning opossessions data collected in a contemporary roupof hunter-gatherers.n a paper on economic changesamongMbuti hunter-gatherersf the Teturiregionofeastern Zaire, Ichikawa (I99I:I42-43) reports data onthe material possessions of i2 individuals in I980.Hunting s a major preoccupation n this group,whichis relatedbypatron-client ies to agriculturalists earby.Meat trading nd wage labor create a commercial out-look and establish inks to the arger conomy.Hunting

B p33 39

K V RR

R R

FIG. 3. The lattice ofthe dual ordering fconsumerdurables and households in Papeete. A, automobile;B, bicycle; F,refrigerator;,kerosene orgas stove; P,primus tove;R,radio; V, two-wheeledmotor vehicle.TABLE 3ReducedData SetforPresence i) or Absence (o) ofSeven ConsumerGoods for 0 Households in Papeete

HouseholdNumber f NumberAFKVRBP Households forLattice0000000 I 40OOOOOIO I 33OOOOOOI 6 39OOOOOII 8 32OOIOOII I 23OOOIOII I 24OOOOIII 6 22OOIOIII I IOOIIOII 2 7OOOIIII 4 I6OIOII0I 2 I2OOII01I 2 9I0 IIIII 3 5IIIIIII 2 2NOTE: A, automobile; , bicycle; ,refrigerator;,kerosene rgasstove;P,primus tove;R, radio;V,two-wheeled otor e-hicle.



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Volume34,Number4, August-October '993 1475is organized n a communal andfamily asis usingnets."The Mbuti still dependonthe traditional unting ech-nologyrather han the traps of steel wire mainlyusedby the villagers.... Theycannot afford o buythe newtechnologywhich would enable them to hunt ndividu-ally" Ichikawa 99i:i59). The possessions able col-lected by Ichikawa in I980 reveals a mixtureof tradi-tional ndmodern oods I99I:I44): "Even t this imetherewere some industrialproductsfrom he outsideworld, uch as cooking pots, enamel ware and printedcloth owned by all the Mbuti." Preprocessing f theMbuti data eliminated ome possessions for he reduceddata set (table 4). The implicationswithsingle-elementpremises re shown n table 5, and figure presents hepartialorder fattributes.Possessionsareordered rom opto bottom ccordingto their requencies. he two top layersof thepartitioncontainbasichunting ools (hunting et,machete,bow)andpossessionsassociated withhunting hoe,dog).Thethird ubset classifiesspecial tools (shovel,tusk ham-mer) ndcheapconsumergoods mortars, poon).At thebottom rare musical instruments nd rare consumergoodsor tools (metal cup, ironpan forgoldmining) readded. At the top lattice analysis detects a basic splitbetweentwo fundamental ossessions,thehuntingnetand the machete. Particularpossessions are clusteredwiththisfundamental ifference:oegoes withhuntingnet; bow, dog, nd tuskhammer refusedwithmachete.I considerthis partition o indicate different untingtechniques:nethunting s communal andpredominant(as the ethnographerells us), but additionally here sanother raditionalnd more ndividualistic ctivity at-tembasedonmacheteand bow which has escapedeth-nographic crutiny. hen,at a morerefinedevel,specialtools and consumergoodsareaddedto these fundamen-talpossessions shovel, nvil,smallmortar, poon),andhere the differentuntingpatterns re cross-connectedTABLE 4ReducedData SetforPresence i) or Absence (o) ofMaterial Possessions amongMbuti Hunter-GatherersH B M h s I A 0 o C N D m k d IndividualI 0 0 I 0 0 0 0 0 0 0 0 0 0 0 II I I 0 I I 0 0 0 0 0 0 0 0 0 III I I0 I I 0 0 I O O 0 0 7I I 0 I I 0 I 0 I I 1 0 0 0 9I I 0 0 0 I 0 0 0 I 0 0 4I I 0 0 0 I 0 0 I 0 I O 0 5I I 0 0 0 01 0I I 0 0 I 20 I I 0 0 0 0 I 0 0 0 0 0 I 0 I20 O I 0 0 0 0 0 0 0 0 0 0 I 8I I I I I 0 0 I 0 0 0 0 0 0 I 10I I I I 0 0 1 0 0 0 0 0 0 0 1 3

NOTE: A, anvil; , bow;C, metal up;D, drum; , dog;H, hunt-ingnet;h,hoe; , ron anfor oldmining; ,tusk ammer; ,machete; ,bamboolutes; ,spoon; , largemortar;, smallmortar;, shovel.

TABLE 5Implicationswith Single-Element remisesamong Mbuti Possessions and Number of CasesFulfilling achPremise Conclusion Number f CasesB M IOh H 3s HBM 5I HMBs 4o BM 5o HBM 2C HBMN 2N HBM 3D HBMO Im HBMON Ik BM 2d M 3NOTE: B, bow; C,metal up; D, drum; , dog; H, hunting et;h, hoe; , ironpanfor oldmining; , tuskhammer;M, machete;m, bamboo lutes;N, spoon; 0, largemortar; , small mortar;s, shovel.by special possessions. n addition, he rare temsat thebottom o-occurdirectly r ndirectlywithmanyoftheothers.These infrequent ossessionsestablish greaterthan usual degreeof specialization (in music or goldmining)or wealth (metal cup as an indicatorof valu-ables).A deep nterpretationfthis magewouldrequiremoreethnographicnformationn the use andmeaning

H Mh d

kI ~~~~~L C

FIG. 4. Thepartial orderof material possessionsamongMbutihunter-gatherers., anvil; B, bow;C, metal cup; D, drum; d, dog; H, huntingnet;h, hoe; I, ironpan forgold mining; k, tusk hammer;M, machete; m, bamboo flutes; N, spoon; 0, largemortar; , small mortar; , shovel; i, absence ofall items.



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476 CURRENT ANTHROPOLOGYof possessions. In addition,the ethnographeroes notcomment n the fundamental ifferenceetweenhunt-ingtechniquesdetectedbythe formal epresentation. tthe level of raw observations, erhapsthis differencewas cloudedbycross-connectingpecial goods. In con-trast, he formaldissectioncan trace differentmplica-tionalpathsand thereby eveal hiddenordering atternsin a reliableand systematicway. Thus a formal epre-sentation uch as figure can be veryusefulto ethno-graphicnterpretationecause it breaksdown thestruc-turalskeletonwhich is oftennot fullyevident to theparticipant bserver.The logical expressions ftable 5specify ifferentmplicational hainsand their requen-cies in the set ofactors.These are typical "possessionspaths." n the Mbuticase there s no overallchaining fpossessions themain finding f the stratified ahitiandata set). Many implications associate special goodswiththe fundamental unting raits.This indicatesthesharing f manytypesofpossessions. It is interestingthatmany logically possible combinationsof posses-sions do not occur empirically.Thus some goods areassociatedonlywith certain thers ndnot inkedto thewholeset (fornstance, , C, d,h). The missing inks or"structural oles") in thedata areclearly vident n theimage; theyshow the nonrandomnatureof the Mbutidata.4To me theordering fpossessions n figure rep-resents undamental nd finedistinctions f hedivisionoflabor in a hunter-gathererommunity:first basiccontrast etweenhunting echniques, henconsiderablesharing f typesof special possessions, and last somewealthdifferentiationnd occupational pecialization ntheset of rarepossessions.Figure5 is a line diagramofthe lattice for heMbutidata.The orderingfpossessions s a bit more elaboratethan n figure , butthe fundamental plitbetweenthetwodifferentypesofhunting ctivities s visible at thetop, nd thespecial tools and consumergoodsare addedfartherown.The ordering factors, ntirelyacking nfigure , is mostrevealing. irst,n theupperpartofthelatticeone can distinguish heset of actors , 8,and 2.These actorshave fewerpossessionsthanthe others nthesample.Most actorsareplaced in the middle of thelattice,whichmeans thattheyownmoregoodsand se-lectsimilarones. Deviatingfrom hiscommonpattern,thetopmost ctors eem to be pooras well as outsiders.Concerningconsumerpreferences he lattice revealsthatactor is an antipodeto actors 8 and I2. Actorspecializes in net huntingby possessingnet and hoe,whereas actors 8 and I 2have no net-huntingools andassociate themselves with the machete/bowhuntingcomplex. nternally,ctors 8 and I2 contrast ypossess-

ing machete/dog, n the one hand, and machete/bow/mortar/tusk ammer, n the other.All the other ctorsown bothhunting et and bow and machete, ombiningthe differentunting atterns nd adding pecial items.The reduceddata set of table 4 shows considerable ver-lap among rows as well as some individualdeviation nthepossession ofparticular tems. n the atticethe shar-ing of typesof possessions is depictedby an abundanceof ross-connectingines n the centre fthe mage ead-ing to similar possession points. Subset or individualpreferencesre indicated by moving actors away fromthe centre the poor and outsidersdepicted at the top)or by locatingthem to that part of the centre bottomleft, ight,middle) which accords with their pecial se-lection of possessions. The lattice representationhowsthatwe candistinguish articular ndividuals ccupyingdifferentositions n the possessions structure y con-sidering he ownership frare tems. Looking t the dataand the image offigure this seems immediately vi-dent, ut exploration f tructuren Ichikawa's raw data(I99I:I42-43) would certainlybe a difficult ask. Thespecific rdering attern mong possessions and actorsbecomesvisibleonlywhen the dataare preprocessed ndsystematically ecomposed. Regarding he differencesamong ctors, ctor 9, for nstance, s wealthy nd mod-ern, wning n ironpan and a metalcup but noneofthemusical nstruments. ctors7 and 2 are similar o 9 butless affluent, ossessingeither an iron pan or a metalcup. Actors4 and 5, owningdrumand bamboo flutesrespectively,re the musicians of the group. Overall,however,below the subset ofpoor outsiders here s alot of connectedness mong actors in terms of sharedtypes fpossessions.This clustering atterns evidenceof the egalitarianpossessions structure hatmightbeexpected n a bandofhunter-gatherers.To summarize, attice analysis of Ichikawa's Mbutipossessions data extractsa fundamentaldifferencenhunting echniques nd then an elaboration f his basicpattern y special tools,commonconsumergoods,andrarepossessions.The ordering f tems seems to be in-ducedmainlybythe divisionof abor nd differentctiv-ity patternsn the group.The ordering f actorsparti-tions outsiders from core members. There are somedifferencesn occupational specialization and wealthamong ctorsdue to thepossessionofrare tems,butonthewholethe members f hisgroup ossess many imi-lar items.Thus latticeanalysisofthepossessionsdatashows that in I980 the Mbuti had adopted manyim-portedgoods,but meat trading nd wage labor had nottransformedhe rather galitarian haring fbothself-produced ndWestern ossessions.Structurally oth Tahitian and Mbuti data sets aresimple,and in both cases pattern ecognitions ratherstraightforward.hathappensto latticeanalysisofma-terial ulturewhenthetask s moredifficult? ow doesthe method opewithmore tems, larger et ofactors,and a more diffuse attern fsharing?An empirical n-swer to thismethodological uestion emergesfrom nexaminationof data on materialpossessions in a Ja-vanesevillage.

4. For ll thedata ets nalyzedn thispaper conductedn overallstabilitynalysis. singproceduresn UCINET IV (Borgatti,ver-ett, nd Freeman992), I constructed atrices f thesameorderas the mpirical ata ets, illed hesematrices ith andom um-bers, nd correlatedherandommatriceswith heempirical atasets nthe terativeuadraticssignmentrocedure.heempiricaldata sets werenot statisticallyignificantlyorrelated ith therandommatrices; hereforehe structuren these (sometimesrathermall) mpirical atasets s not due to chance.



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Volume 34, Number 4, August-October I993 477

Hdh

12

FIG. 5. The lattice ofthedual ordering f material possessions amongMbuti hunter-gatherers., anvil;B, bow; C, metal cup; D, drum;d, dog; H, huntingnet; h, hoe; I, ironpan forgoldmining; k, tuskhammer;M, machete; m, bambooflutes;N, spoon; 0, large mortar; , smallmortar; , shovel.

A COMPLEX CASEData on the materialpossessions ofJavanesepeasantswere collected as part of an anthropological tudy ofthe rural conomy n a rice-producingillage n CentralJava by Margarete Schweizer and myself n I978-79(Schweizer 987, i989). The data set consists ofbinarydata on the presence/absenceof 34 consumer itemsamong 98 households roughly ne-third f thevillage;in the lattice analysis the reduced data set uses 7Ihouseholds nd 26 items).The observations over hous-ing,furniturend consumerdurables, nd livestock.The backboneofclass stratificationn ruralJava, if-ferentiatingn upper lass ofvillage officials,arge-scalefarmers, nd rich merchantfamilies, middle class ofsmall-scalefarmers,enants, raftsmen,raders, nd fac-toryworkers, nd a lower class of farm aborers nd ca-sual workers, s ownershipof irrigated and. The ma-jorityof people in the village earn their iving n theagrarian ector, ut 43% ofhouseholds are andless.Off-farm mployment, ideline activities, easonalityof a-

boruse, and migration o the cities are importantn-come-producing trategiesforthe village population.Thus Javanese illages are deeply mbedded n the argersociety, nd since the igth centurymanyWestern on-sumergoodshave diffusednto thecountrysidendbe-come part f ocal life-stylesAlexander, oomgaard,ndWhite 99i, Schweizer 993b).Wealthdifferentialsindvisible expression n differenttandardsof living anddifferentabits of consumption.Class differentiationsmediated to a certain extent by crosscuttingkinshipties, neighborhoodobligations, religious affiliations,and common ritualactivities Schweizer,Klemm, andSchweizer993). Thisextends o thecommunal se ofsome valuable materialpossessions. For instance, mo-torbikes an be lentout if needbe; neighbors egularlymeet in the home of theirrichpatronto watch televi-sion; kerosenepressure amps and furnituremay besharedat festivals.Thus cultural rules and socioeco-nomicconditionsgenerate rather omplex social sys-tem with class stratification nd life-style ifferences,



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on the one hand,but also a considerable mountof har-ing of goods and commontraditions, n the other.How can lattice analysis decompose the interlockingorder f ctors nd possessions n this Javanese ataset?As participant observerswe had difficulty reakingdown this structure ystematically. partfrom basicclass differencemonghouseholds andtheir ossessionswe noted typical co-occurrencesmong particular on-sumer items and many exceptions n detail. The fre-quencies and the prices of consumer items providedclues to their economic and cultural values, but thewhole patternwas ratherdiffuse.A factor nalysis ofthedata detected 4 orthogonal actors ndthusrevealeda rather omplicated tructure f co-occurrencesmongthe consumer tems Schweizer 989: 236-39).Given such a largeand complexdata set, the latticeof the total (even reduced)data matrixwill be nearlyincomprehensibleecause all the mplicational elation-shipswill be displayed n one overcrowded mage.Eventhe mageofthepartialorder f attributeswill be hardto read. Thus it is wiser to begin by studying ubsetsofthe items (housing,furniture/durables,ivestock) todetectpatterns eparately or ach domain. t t also use-ful to conductmoreabstract nalysesofthewhole dataset to representheoverall ordering attern Duquenneigg2b).This data reduction acrificesdetail in order ograsp tructure.n thispaper shall skipthepartial nal-yses and present ome findings rom bstract nalysesof he data set as a whole. Two different ethods fdatareductionwill be employed.The first nd moreradicalone fuses ttributesndobjects ntoblocks according othe regularity f their relationshipswith membersofother blocks. In this procedurewhat is ordered s notindividual objects and attributesbut more abstractblocks representingets ofattributes nd objectswhichoccupysimilarpositionsin the structure.n this datareductionvia grouping here s no longer one-to-onemappingbetween the data and the blocked attice. Theimage producedbythisblockingprocedure s compara-bleto a technical xplosionwhereby oints re stillcon-nectedbut movedapart oprovide nsightnto the struc-tural skeleton. The technical term for this blockinganalysisand the visualizationof ts results s gluing. nthe analysis of a data set withinthe gluing procedureofGLAD, the programwill always detect an identicalgluing tructure, utoptimizing hepicture an lead toa morerevealing mageofthepattern. he secondproce-dure of data reduction s called boxing. n boxing omelines ofminor mportance reerased o ncrease he clar-ityof the image. Generallyboxing preserves he corre-spondencebetweenthe image and the data. However,in a complexdata setboxingmaybe less successful hangluing s an aid to pattern ecognition.Figure presents n overall mageofthe dual orderingfor he whole set ofmaterialpossessions (from he re-duceddataset)based ongluing Duquenne i992a:8-Io).Those items and actors have been fusedtogetherntoablock which stand n thesameregular rderingelation-shipto members f otherblocks.Thus the tems/actorsin a blockare interchangeablen thatthey tand n the

same sharing relationship to elements in the otherblocks above or below them and thusgenerate he sameorderingonblock modelling ndregular rder n general,see Borgatti nd Everett 992). Membership n a blockdoes notnecessarilymean that the substitutable temswithin t are simultaneously resent n a household al-though they may be); however, any item present n ablock is absent in a block located above it along as-cending ines. Hence an actor n a particular lock couldpossess anyof the itemscontained n the blocks aboveit but none of those n the blocksbelow it. From top tobottom he blocksare ordered ccording o wealth. Thushouseholdsat the top are poor, whereas those at thebottom re rich and those fromblocks in between arein an intermediate osition. tems at the top are high-frequency oods with (often) ow economic value; pos-sessionstowards hebottomofthe lattice are rare nd/or expensive. nfigure the firstine of he abel for achblock mentions he tems frombovetypically hared nthe block,while the second line mentions the crucialnew possessions added to the pattern n this block. Thebreakdownof materialpossessions in figure6 revealsthathousingfeatures re most fundamental or he or-dering structure;furnishings/durablesnd then live-stockare addedas subsidiary ossessions to enrich ndrefine he basic pattern. n Bourdieu's terms I979) theoverallblocking tructure evealsfundamental lass dif-ferentiationinthisagrarian ocietymainlydeterminedby landownership nd occupation),whereas at a finerlevel of lassification articular locks can be consideredas typical ife-styles"habitus")ofparticular lass frac-tions.In block i offigure is displayed heset ofcommonpossessions (remember hat these items need not bepresent n full n each householdof the block): owner-ship of a house, brick not concrete)floor,brick (notbamboo) walls, well, bathroom, argehouse,setof bam-boochairs ndtable,radio,wristwatch, icycle, nd ban-tam chickens. would hesitate to say thatthese itemsrepresent he typical patternof possessions of poorhouseholds, utclearly hey recommon, ndpoorfam-ilies do not in principle wn anythingmorethan thesewidelydistributedtems.Theydo nothave access to thevaluablegoods in the lowerblocks,and in reality heyoften wn onlya fraction f the items of thetopblock.The households mentionedas the typical examples ofthefirst lock ndeedbelongto the ower-class egmentofthevillage; they arn their ivingfrom arm abor andcasual labor and have onlya fewpossessions, confiningthemselves o necessities.Below the fundamental first block the patternbranchesntotwo differentathsbycharacteristicelec-tion of temsfrom bove and additionofnew elements.The branching o the left reflects more traditionalmode ofconsumptionwhich s moreagrarian/livestock-oriented,whereasthe blocks to the right endtowardsmoremodern, rban-influencedife-styles.Inblock2 people ive in their wn brick-walled omesand keep ducks as a moderatecapital investment, heregular are ofwhich is a full-timeob forone member



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480 I CURRENT ANTHROPOLOGYhouse, invest in better iving conditions. There is norenting f houses in the village, so people living n ahouse not theirown are oftenresiding n the house ofrelativeswho eventuallygive t to them. Alternatively,the landlord s a migrantwho prefers o have someoneoccupy the house because otherwiseghostscould in-trude nd make the place uninhabitable.The people inthe fourth lock also enhance theirhomes with mat-tresses and sets of plastic chairs and tables. This isclearly a more modern style of living preferred yyoungerpeople. A typical case is the household of ayoung ouple in their wentieswith three hildren, iv-ing n a house whichbelongs to the husband's aunt. Hestartedwith casual workin an iron-processing actoryoutside the village and now earns a considerablewageas driver orhis boss. His personal ife-styles urban-influenced: e wears blue jeans, reads comics, istens topop songs,and smokes manufactured igarettes, ll ofwhich contrast tronglywith thepattern f traditionalbatik clothing, amelanmusic, and self-produced iga-rettes ypical f his parents, is spouse, and many othermore traditional illagers.In blockS this modernpatterns more elaborate.Thehouses are bigger ecause ofthe age and householdcycleof theiroccupants-people in their hirtieswith largerfamilies. hese people buy middle-class onsumer temssuchas water losetsandsewingmachines.Trade oftena femaleoccupation)and better-paid ositions n facto-riesprovide teadyhigherncomes. Farming,fpracticedat all, is a sideline. Members of this block belong tothe ruralmiddleclass. People ofblocks 4 and 5 do notspecialize in livestock, nd farmings secondary.Block 6, at the bottom of the lattice, s occupied bytheuppermiddle andupperclass of thevillage.Here allthehousingcharacteristics re fused:people live in bighouses of their wn with brickwalls and wells and mayhave all the items from he upper blocks. Among theset ofspecial possessionsoccurring or he first ime nthis block are some rare nd expensiveconsumer temsand some capital investments:kerosenepressure amp,television et,wall clock,alarmclock, motorbike, edi-greedchickens,Manila ducks,and waterbuffalo. ive-stock s rearedbythese households as an occupationalspecialization, nd the investment s considerable.Buf-faloes re used as draughtnimals for loughing hericefields.A look at the households classified n thisblockclearly eveals their uperior osition.Heterogeneousnageandoccupational pecializationbuthomogeneousnterms fhigh ncomes,this block containswhite-collaremployees,wealthyfarmers,uccessfulmerchants,ndvillageofficials.Summarizingthe dual ordering tructure, igure6demonstrates he prevalenceofhousingcharacteristicsas indicators f economic welfare incidentally,he Ja-vaneseuse housing s an indicator fwealth).Thenpos-sessions are subdivided nto a traditional grarian at-tern with specialization in livestock keeping and amodernpatternwith urban-influencedife-style ea-tures. n theupper-middle-nd upper-classblock thesetendencies re fusedand furthernrichedby expensive

consumer tems and capital goods. Thus in the set ofpossessions we can observe hierarchicalwealth differ-ence but also a rural/urban ontrast n tastes and eco-nomic specialization (agrarian vs. nonfarm/modern).Among he set of actors attice analysis reveals a gradedorderingnto ower-class blocks and 2), lower-middle-class (blocks 3 and 4), upper-middle-classblock 5 andpartsof 6), and upper-class block 6) positions. Thesegraded positions are characterizednot only by differ-ences in occupation, ncome, landownership, nd thuseconomic capital but also by differencesn age and stagewithin hefamily ycle. At the evel of householdsgen-der eems to be less important s a factor n the distribu-tion of materialpossessions (within households, how-ever,there s important ge and genderdifferentiationof possessions).Figure is a breakdown f the upper-middle-nd up-per-classblock at the bottom offigure . This is not agluing issectionbuta partial nd simplified epresenta-tion ofa sublatticeof the raw data based on theboxingprocedure Duquenne i992a:8-Io). The ascending inescan be read as strict mplications,and the clustereditems re nvariably resentnthe householdsthey on-nect to.Figure revealsthat herich re subdivided ntoseveral subsetsby livestock variables. This maybe anunexpected finding, ut it makes sense ethnographi-cally.The subdivision s inducedbydifferentevels ofwealth and by occupational specialization. Top-down,householdsare contrasted y livestockkeeping.Belowthe upper subset without any livestock there is abranchingnto capital-intensive uffalokeepingto theleft, nexpensive hickenkeeping n themiddle, nd in-termediate-leveloat keepingto theright.The subsetsare establishedby differentombinations of livestockitems. Overall I see a nonagrarian pper pattern ndbelow a division into large-scale (buffalo), ommon(chicken), nd small-scale (goat) agrarian atterns.Themainfinding fthis n-depth iew of theupperandup-permiddleclass is thatthe richesthouseholds subset )arenot those with the most materialpossessionswhenlivestock s included. n contrast o the housingattri-butes and consumerdurables,whichfollow an additivepatternthemore ffluent ouseholds re, he moretheypossess of these items), ivestock is not just added asanother sset to thepattern utmakes a significant if-ference. ivestockkeepingbreaksapartthe upperanduppermiddle class in accordancewith capital, activitypatterns,ndoccupational pecialization.First, herich-estpeoplein thevillage subset ) do notkeeplivestockat all. Wealth is measured independently f materialpossessionsby consideringandownershipndmonetaryincome.These people ("thereal elite"),whose status sthehighest n thevillage,earn their ncome in the off-farm ectorsof services and trade or from arge-scalericegrowingwithhired abor.They ive nbetter-qualityhomesand amass consumergoods,but livestock s notpartof theirhabitus.Second,householdskeeping ive-stock are esswealthy n terms f and and income thanthe first roup.They keeplivestock s a sidelineandaresubdividedfurther y the amount of capital theycan



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Volume 34, Number 4,August-October 1993 I 8Isubset

subsetsubsetFIG. 7. Breakdownofmaterial possessions and households n theuppermiddle and upperclass in a Javanesevillage. A, bathroom;b, bamboo furniture; , ducks; f,brickfloor;g, goats; H, bantam chickens; L, kerosenepressure amp, 1,plastic furniture;m,Manila ducks; r,radio; s, sewingmachine; T, mattresses;U, waterbuffalo;V, television et; W, wristwatch;Y, bicycle.invest n this specialty. n moredetail the subsetscanbe described s follows:Subset is characterized y the absenceof ivestock.It containsthe most affluent eople of thevillage,whoearntheir ivingfromwhite-collarobs as employeesorvillageofficials. his village elitedoesnot nvest n live-stock because moreprofitable entures re available toit. In the village its members hire labor, includingdraught nimals,to work n their icefields. utsidethevillage hey pendon higher ducationfor heir hildren,business riceor retailtrade, ransport),r and for ash-crop roductioncloves seeSchweizer990:270-74]).Subset 2 is a bit exceptional,because it is veryrarefor grarian ouseholds tokeep onlybuffaloes. ere thefine-grainedattice dissection detects an exception o abroad culturalpattern. he household representative fsubset exhibits n agrarian pecialization. These peo-ple own ricefields ut in addition are tenants nd workas laborerswith their draught nimals ploughing thefields fothers.Subset 3 is a continuation f this pattern. n additionto buffaloes hese familieskeep bantams.Typically heyare richfarmerswith a considerable mount of and of

theirown. This land is worked with draught nimals,and ifthere s slack time farm abor using the buffalobecomesa sideline.Subset 4 contrastswith the elite subset by chickenkeeping.The households n this subset are less affluentthan thoseofsubset , but they re in a good economicposition.They own land, some people earntheir ivingas merchants, nd there re also retiredwealthypeople.Subset5fuseshouseholdsengagedngoat keeping ndchickenkeeping.Goatsare ess expensive hanbuffaloesandneed less care. In subset 5 we findhouseholdsthatengage n cattlekeeping s a sideline, heirmainoccupa-tion being farming,arm abor,orfactorywork. n thissubsetthere re several widowswith childrenwho carefor hegoats.To summarize, he image in figure yields a subtlebreakdown of capital and occupational specializationamongmembers ftheupper nduppermiddle classes.Particular ombinations fkeyvariables livestock),ma-jor ubgroups, nd even exceptions o theoverallpatternare detected.What ooked in the macroscopicview likea fusion of agrarianand modern possessions in thewealthyblock at the bottomoffigure is disentangled



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in the n-depth nalysisof figure . The affluent ouse-holds n this villageare set apartfrom he ess wealthyvillagers ot ust by a higher evel ofpossessions this sthe mpression rom he overallview); the mageof thesublattice clearly shows that capital-dependentive-stockspecialization s involved n the internaldivisionof the uppermiddle and upper class. The breakdownreveals he nterestinginding hatthe peoplein thevil-lagewho arehighest n housing nd durables s well aslandand ncomedo not possess livestock t all, whereasupper- ndupper-middle-classouseholdswith ess cap-ital and land keep livestockas a sideline.DISCUSSION AND CONCLUSIONWhatdowe gainby applyingattice nalysistomaterialpossessions data? Data on material possessions areintrinsicallymeaningful or he studyof thefundamen-tal organizational rinciples nd the basic scaffoldingfsocieties.Presence/absence ataonmaterial ulture rewidelyavailable in ethnographic, istorical, nd evenarchaeological ecords ndvery evealingwith regard osocial hierarchies nd the divisionof communities c-cording o age, gender, ccupationalspecialization, tc.Atthe heartof materialpossessionsdata are logical m-plications nd thenotion of dual ordering. he availablequantitativemethodsgenerally o not recover nd repre-sent implications, ut this task is fundamental or hestudyofmaterialculture rrespective f the particulartheoretical erspectivedoptedfor nterpretinghe data.Lattice analysis represents he empirical possessionsdatain a formalmodel.The crucial nformationn themeaningand use of the items or the characteristics fthe actorshas to be addedfrom heethnographicecord.The formal magerevealsthe structuralkeletonof thedata: it traces all implications nd displays hedual or-dering fpossessions and actors. This visualizationofoften omplexdata enablesdeeperunderstandingf theinherent rdering attern nd provides spurto ethno-graphicnterpretation.I haveapplied attice nalysisto threedifferentmpir-ical cases. In the Tahitian case, the methoddetecteda hierarchical hainingofpossessions and an ensuingstratificationf households. In the case of the Mbutihunter-gatherers,ossessions were decomposed intofundamental unting raits ndcross-connectingpecialgoods, nd the set ofactorswas brokendowninto out-siders nd coremembers.The lattice magesclearlyre-vealedthedivisionof aborand theegalitarian istribu-tionofpossessions.Latticeanalysisof theJavanese ataled, on the one hand, to a regularordering f hous-ing, furniture/durables,nd livestock items and, ontheotherhand,to a pattern fclass and class fractionsamongthe set of actors. Class differentiation,houghfundamental,s byno meanstheonly ourceofvariationin thedual ordering attern.Age,occupationalspecial-ization,and stagein thefamily ycle createadditionalorderingsmong possessionsand actors.As these examplesdemonstrate,attice analysis is apowerful ool forrepresentinghe logical implications

andtheensuingdual ordering attern n thesedata. De-pending n the complexity f the task at hand, we canstudy he ordering f attributes y focusing n implica-tionswithsingle-element remises a condensedstruc-turalview); we can analyze the whole set of ogical im-plications n the input data and the ordering f bothattributes nd actors n the attice;we can conductpar-tial analysesof ubsetsofthe tems or actors.The gluingandboxingbreakdowns re more or less powerful oolsfor issecting nd representinghe total ordering atternin abstractways. Thus lattice analysis s a veryprecisemethodforstudyingglobal implicationalstructure swell as fordetecting pattem in material possessionsdata. Current ffortsn thefield fdiscrete ata analysisare providing rograms nd empirical examples of theuse ofdiscretemethods n the social sciences.There smomentumfor inking ubstantiveproblemswith for-mal solutions.A more complete nvestigation f theJa-vanese data is in progress,nd in a secondary nalysisam assessing PollyWiessner'sethnographic ata on thematerialpossessionsof the KungSan ofBotswana seeWiessner982:79-83 for n overview),xtendinghestudy fmaterialwealth n contemporary oragingoci-eties.Furthermore,hereas have focusedhereon pat-temsofconsumption n these communities t a singlepoint n time,Whiteand Scudder n.d.),analyzingpos-sessions datafrom lizabethColson's and Scudder's on-gitudinal tudyof the GwembeTonga in Zambia, com-paredifferentemporalpatterns n the acquisitionanddistribution f goods. Thus the elementof time mayeventuallybe studied systematically nd precisely ndiscretemodels of materialpossessions.References itedALEXANDER, PAUL, PETER BOOMGAARD, AND BEN WHITE.I99I. Editors.n the hadowof griculture: on-farmctivi-ties n theJavaneseconomy, ast andpresent. msterdam:RoyalTropical nstitute.APPADURAI, ARJUN. I986. Editor. he social ifeofthings:Commoditiesn cultural erspective.ambridge: ambridgeUniversityress.BERNARD, H. RUSSELL. I988. Researchmethods n culturalanthropology.ewbury ark:Sage.BISHOP, YVONNE M. M., STEPHEN B. FIENBERG, AND PAULW. HOLLAND. 1975. Discretemultivariate nalysis:Theoryand practice. ambridge:M.I.T.Press.BORGATTI, STEPHEN P., AND MARTIN G. EVERETT. I992.

Regular lockmodelsfmultiway,multimodematrices. ocialNetworks4:9I-I20.BORGATTI, STEPHEN P., MARTIN G. EVERETT, AND LINFREEMAN. i992. UCINET IV. Columbia, .C.: Analytic ech-nologies.BOURDIEU, PIERRE. 1979. La distinction: ritique ocialedujugement.aris:Editions e Minuit.BURMEISTER, PETER. I99I. Begriffsanalyseufdem BM-PC.Fachbereich athematik,echnischeHochschule armstadt,Darmstadt.CASTRO, ALFONSO PETER, N. THOMAS HAKANSSON, ANDDAVID BROKENSHA. I98I. Indicatorsfrural nequality.World evelopment:40I-27.DEGENNE, ALAIN. i992. Mutual helpbetween ouseholds:Anexample fBoolean nalysis. ocial Networks S. Inpress.DEGENNE, ALAIN, AND MARIE-ODILE LEBEAUX. i992. Ana-



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Volume34, Number4, August-October I993 1483lysebooleenedesquestionnaires:rogrammeOOLEEN,Ver-sion i/o9/92. Paris:LASMAS-IRESCO.DOUGLAS,MARY, AND BARON ISHERWOOD. I979. Theworldofgoods:Towards n anthropologyfconsumption.ondon:AllenLane.DUQUENNE, VINCENT. i992a. Models ofpossessionsndlattice nalysis.MS, CRNS andMaisondes Sciencesdel'Homme, aris.. i992b. General lattice analysis and designprogram(GLAD).CRNS and Maison desSciencesde l'Homme,Paris.ELSTER, JON. I98I. Snobs.LondonReviewofBooks,November5-I8, pp. IO-I2.FEATHERSTONE, MIKE. I99I. Consumer ulture nd postmod-ernism.London: Sage.FERGUSON, JAMES. I988. Cultural xchange:Newdevelop-ments in the anthropology fcommodities. Cultural Anthro-pology :488-5 I 3.. i992. The cultural opographyfwealth:Commoditypaths nd the tructurefpropertynrural esotho.AmericanAnthropologist4:55-73.FREEMAN, LINTON C., AND DOUGLAS R. WHITE. I992. "Us-ingGallois attices orepresent etwork ata," nSociologicalmethodology993. Edited yPeterV. Marsden. anFrancisco:Jossey-Bass.npress.

GIFI, ALBERT. I990. Nonlinearmultivariatenalysis.Chiches-ter:Wiley.HAGE, PER, AND FRANK HARARY. I983. Structural odels nanthropology.ambridge: ambridge niversityress.. I99I. Exchangen Oceania: A graph heoreticnalysis.Oxford: larendon ress.ICHIKAWA, MITSUO. I99I. The impact fcommoditisationntheMbutiofeastern aire. Senri thnologicaltudies 0:I35-62.KAY, PAUL. I964. A Guttman cale modelofTahitian on-sumer ehavior. outhwestern ournalfAnthropologyo:I60-67.KLOVDAHL, ALDEN S. I98I. A noteonimages fnetworks. o-cial Networks:I97-2I4.LANG, HARTMUT. I993a. Who urvived?A reanalysis of theDonner arty. aperpresentedt the Sunbelt ocialNetworksConference,ampa,Fla.,February.. I993b. The logicofdowry ndcompetition: reanalysis.MS, nstitutefEthnology, niversityf Cologne.MC CRACKEN, G. I989. Culture nd consumption.rbana:Uni-versity f llinois Press.MILLER, DANIEL. I987. Material ulture nd mass consump-tion.Oxford: lackwell.RUTZ, HENRY J., AND BENJAMIN S. ORLOVE. I989. Editors.Thesocialeconomy f consumption. anham:UniversityPress of America.SAHLINS, MARSHALL. I988. Cosmologies ofcapitalism: hetrans-Pacificector f "theworld ystem." roceedings ftheBritish cademy 4: -5 I.SCHWEIZER, THOMAS. I987. Agrarianransformation?ice pro-duction na Javanese illage.Bulletin f ndonesian conomicStudies 23(2):38-70.1. 989. Reisanbau n einem avanischen orf.Cologne:BohlauVerlag.1. 990. A centuryofchange in the Javaneseruraleconomy:Contrastingevelopmentsnupland nd owlandKlaten. nter-nationalesAsienforum1:259-77.9. 93a. Actor and event orderings cross time: Lattice rep-resentationndBoolean nalysis fthepolitical isputenChenvillage, hina.SocialNetworkss. Inpress.. I993b.The cultural se ofthings: onsumptionnruralJava. ndonesiaCircle6o. Inpress.SCHWEIZER, THOMAS, ELMAR KLEMM, AND MARGARETESCHWEIZER. I993. Ritual as action in a Javanesecommunity:A networkerspectivenritual ndsocialstructure.ocialNetworks 5. In press.THOMAS, NICHOLAS. I99I. Entangled bjects:Exchange,mate-rialculture,nd colonialismn thePacific. ambridge: ar-vardUniversityPress.

TUFTE, EDWARD R. I983. The visual display f quantitativen-formation. heshire:Graphics ress.VOGT, FRANK, AND JORG BLIESENER. I99I. Diagram rogram.Fachbereich ath'ematik,echnischeHochschule armstadt,Darmstadt.WELLER, SUSAN C., AND A. KIMBALL ROMNEY. I990. Metricscaling:Correspondencenalysis.Newbury ark:Sage.WHITE, DOUGLAS R. I99I. Statistical ntailmentnalysis ro-gram. epartmentfAnthropology,niversityfCalifomia,Irvine.. I992. PGRAPH .oo. Kinship etwork nalysis oftware:Programnduser'sguide.DepartmentfAnthropology,niver-sity f California,rvine.WHITE, DOUGLAS R., AND VINCENT DUQUENNE. I993. Edi-tors. ocial networknddiscrete tructurenalysis. ocialNetworks S. Inpress.WHITE, DOUGLAS R., AND PAUL JORION. i992. Representingandanalyzing inship:A newapproach. URRENT ANTHROPOL-OGY 33:454-463.WHITE, DOUGLAS R., AND H. GILMAN MCCANN. I988."Citesandfights:Material ntailmentnalysis ftheeigh-teenth-centuryhemical evolution,"n Social structures:networkpproach. dited yBarryWellman ndS. D. Berko-witz,pp. 80-440. Cambridge: ambridge niversityress.WHITE, DOUGLAS R., AND THAYER SCUDDER. n.d.Social dif-ferentiationnd material cquisitionnGwembeTonga.MS,DepartmentfAnthropology,niversityfCalifornia,rvine.WHITE, DOUGLAS R., JEFFREY STERN, LILYAN BRUDNER-WHITE, AND HUGO F. NUTINI. I993. Conflictsfconsensusin socialcognition: elief ystemsn a Tlaxcalanvillage.MS.WIESSNER, POLLY. I98 2. "Risk,reciprocity,nd social nflu-enceson Kung aneconomies,"nPolitics ndhistorynband societies. dited yElizabeth eacock nd Richard .Lee, pp. I-84. Cambridge: ambridge niversityress.WILLE, RUDOLF. I990. Concept attices nd conceptual nowl-edge ystems. achbereich athematik, echnischeHoch-schuleDarmstadt, reprint340.

The GeneticStructure fAncientHuman Populations1HENRY C. HARPENDING, STEPHEN T. SHERRY,ALAN R. ROGERS, AND MARK STONEKINGDepartment fAnthropology, ennsylvania StateUniversity, niversity ark,Pa. I6802 (Harpending,Sherry,nd Stoneking)/DepartmentfAnthropology,University f Utah, Salt Lake City,Utah 84II2(Rogers),U.S.A.Differences among human mitochondrial DNA(mtDNA) sequences are an important ource of dataabout the historyof our species. Since mtDNA se-quencesarenotbroken nd reformedyrecombination,they re tipsof a treeofdescent.There are severalap-proaches o usingmtDNA sequences to infer roperties

I. C I993 byTheWenner-GrenoundationorAnthropologicalResearch.All rights eserved OII-3204/93/3404-0007/$I.00. Wearegratefulor omments nd suggestions rom tan Ambrose,AdamConnor,JamesCrow, RichardKlein and Jeffreyurland,OzziePearson,ndNaokoTakezaki.Laboratoryesearch assup-ported n part byNSF grantgo-2o567 to Mark Stoneking.

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