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Journal Title: Ethnobiology 1 Edited by E. N. Anderson, D. Pearsall, E. Hunn, N. Turner. Vol: No: MonthNear: /2011 Pages: Chapter 20

Article: Author: Norbert Ross, Caissa Revilla Minaya; Cognitive Studies in Ethnobiology; What Can We Learn About the Mind as Well as Human Environmental lnteraction?

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Chapter 20

Cognitive Studies in Ethnobiology: What Can We Learn About the Mind as Well as Human Environmental Interaction? NoRBERT Ross Vanderbilt University, Nashville, TN

CAISSA REVILLA·MINAYA

Vanderbilt University, Nashville, TN

CATEGORIZATION AND REASONING

CATEGORIZATION: EXPERTISE AND CULTURE

REASONING: EXPERTISE AND CULTURE

REASONING, CULTURE AND BEHAVIOR

ACQUISITION OF FOLKBIOLOGICAL MODELS: INNATE MODELS AND CULTURALKNOWLEDGE

WHAT IS CULTURE AND HOW DO WE STUDY IT?

CONCLUSION

REFERENCES

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As cognitive scientists we are interested in folkbiology as a domain that allows us to explore the developing mind in phylogenetic and ontogenetic tenns. Everyone has sorne exposure to the biological world; hence comparative research is feasible. Throughout most ofhuman his­tmy, our species engaged with the biological world for survival, so biology might be one domain where evolutionaty biases in our cognitive apparatus-if they indeed exist-are most salient. As anthropologists we are interested in folkbiology for two reasons, which

Ethnobio/ogy. Edited by E. N. Anderson, D. Pearsall, E. Hunn, and N. Turner «;) 2011 Wiley-Biackwell. Published 2011 by John Wiley & Sons, Inc.

335

336 ChaplL'r 20 Cugnitiv.: Studks in l~thnuhiulogy

COllllCL'( (ll the interests or tht: cognitive st:it:ntists. \Ve ask IHI\\" hlllll<lll tltllll)!ht ahllll( the environment relates tu tllL' ways our spet·ies at:h u pon tht• t'll\ inllllltt·nt. Rt•st•ardt in this art•a relates co~nitive wmk with hehavioral studit·s uf" 1\''illlii"L't' mana¡.!t'lllt'lll and l'llllllit·t over resoun.:es,(Atran L'l al. Jl)ll11. 2002; Medin et al. .~!Hllla. :~0117; l{tlss .~001. .~llll2a; Ross et al. 2007). Another inquiry t•xplores the at·quisittott, transrlli'islllll. a11d tr;mslunuation uf knuw kdge. ex plori ng eh i ldren · s karn i IIF. 1 ransm iss Hlll. and t r;mslt 1111 tal in11 ol k IH 1w k•dpt· across cultures ami generatilllls. and loss ol" knuwkd~~l' 1 Atr;m ;md r-.kdin .~Ot!H; :\trant•t ;d. 2004; Ross 2002a.h; Rnss t'l al. 200.\; Stross 1 1J70; \Va\1\l<lll t'l al. .1007; \\'11IIT t'l al. JlJlJlJ;

Zarger 2002a.h; Zarger and Stcpp .~OO·k Zt•nt .~0() 11. Tht•st• studit•s link tltt· two dist·tplines involvcd in tlll' cugnitive rL'seardl ol" folkhiology. and relatt' tht• Wtltk 111 t'llvinllllllt'lltal t•du· ~.·ation. Tllcy cunncct l"olkhiology with tht•url'lical questious rl'i<~ling tn cultme ;urd ~·ultmal proeesses 1 A tran et al. 2005; Ross 21 )( ).J; S ¡wrhL'I' 11JIJ(¡).

We address impurtant as¡lL'cts in t:ulturt• and l."ll~~nititlll hy itHnldut·in,t: vultuf\· inlt1 tlw study uf the mind ami vice versa. lmpurtant and rckvant lilt'l<tllllt' 1'> "Jllt.•ad 11\L'f' a Wllk array ol'journals thal very likl'ly du IHI( rl'ptt'SL'lll tllt' stapk t'l·ading PI any unt.' rt·~·t•ardtt•r;

tiu· L'Xample: .lolll'lltil o/ l·.'tl/1/ohio/ogv; l·."tHiolllit· /lotclfll". l·tlulld'tr 1log\ 1111.! 1-:thno mctlidnt': Currcnt :\ntltm¡'t'lugr: .lnumul o/tlw Roro/ :\nthn'f't'/nglntl .\ot wrr: ( ·,,¡;nttion:

Child !Jcrdo¡llllt'lll: lll\'l'hologit·u/ Nl'l'it•u·: and 11111111111 llit~lt~gr Tht~ ptn\ idt•, a dtalkn¡~t· fur an intq.1ratiw appruadt. "' dillt•tt'lll tht'tiJt'llt\tl and lllt'lltlldllln¡.•tt·al apprnadrt·~ atHI m:hil'VL'llll'llls are ulkn ignmt•d al'Jo'' tht' !Wtl di,l'iplillt'' IRt''' ;tlld t\kd111. in J'l\''-''

[n anlhmpn[ogy the initial lúnt> ha' ht't'll nn tht• t 11/llott ni loiJ...htolltt,l't'·;d knuwblgt' the ducUiliL'lltation ol intrkalt' hllll\\ bl¡•t• '''lt'lll' a' hl'id h~ lndi¡•cnnu' pt•uple !lkrlint•t al. 11)7.1: C'unklin llJ:\ . .1, 1%.~.; haht' !lltd. 1%.1 1 Tlrt• t\uly wo•rk 111 thi' dumain hy Bl'rlin l'l al. tl 1l7.\, 1111·11 pruvcd p;~thhrc;tklll¡' 111 ,,;\ct;d lq'atd• .. hr;,l. i t shmwd tllL' twwssi t y uf i ntt•rd isc í pi í nary tt''l'atdl hy i llt'tllfltlra! i ng !11 11 ;lflt"h and /tlt ,¡, 'l-~ l' .. t­intn largL'"scale t'l~sean.:h prujt•rts. St'l'tHHI. llll' rt·wardt '-t'l ;1 lu¡üt o,t;tnd;nd 111 lt'lllt' ot

systematiL' hutg·tt'nn data t'olkl'tiun in tht• Jil'ld. lht· prnJt'VI '>llll\\l'd th.1t lodh npt·th 11fll'n huid hiologit.:al knowledge L:ontparahk· tn if nrl! t'\n•t•dinv hhl'•"it·rlttli,. J...wm kd¡:~·

Similar projt•L·ts I'PIInwl'd 1 ll;tlt:l. 21 102; Mt'''L'f' I11'J 1; SltqliHd 1'! al .• ~tll ¡,¡; h·11t ;md h·nt 20021. yd partially driwn hy LTitidsm in anthlll(lPltl~~.} lht· i111.·u, ,,¡ llllt'l\''-l t'\parnlnl from doL'lllllL'Ilting sokly grnllf' knulr!t·tlgr tu ""'t.'""ill~~ tltl' dwril111f11111 "1 l.nnH/;·,/gt'

1rithin grou¡1.1 tBtlsll'r lllH7; la Torn• ( 'uadtm attd Rm•. :'t~H. Rll'•" ;100.\r.h .. 1fHI·IJ

Studying knuwledgl' distrihution wa' l'llliann·d hv tlrt• l'llll'l}'lllV 11'•1' ni nunPt"<IIIIJlllll'l' ami tlll' dL'\'L'lopment pf IIL~W statistkal llllllkls .... udt ''" th1• ( 'ultur.tl ( ·PII'>t'll'll" \l1>th'l IRonmey t'l al. I11XItl. whit-h we will dt~SL'J'ilw i111\n\ 20.1. Tht''>l' -.tudh.'' tll\nht·d Jd.altH'l\ little attentitHl totlll' pnK'L'ss ol"thinktng. \\'htllllt' think \\;1; H'JY "llt'll ~lt11hrd mdl'fll..'ltdt·nth ur ltoll" thinkíng (/l"flltlll\' IIIÁt'S '''lll 1' (Ir t\lldntdt.' l 1JX 1; fm óllll'\l'l'J'll• '" '•t'C H .. mdall 111'/(1, 111X7 l. [nt"L~t·ent YL'al"' it J¡¡¡, h~~t.'Dilll' ck;u· tlmt J..ntndnlgl' ll·'flft'flf r.IIHH •l ht• ··t.·p•lló!l<'d ln•m tlw ¡mWt'IIÍng o( injormotiuni l..wlll-lcdgt·.

Rqll'l'SL'lllational sys!L•nts ¡ut• a L'il'>l' in poitll. Culturt• fl111\Ídt•' tH¡.'.IIIIlnl ,\,h'lll'• 11!

knuwblgt' (J r i\ndr<Hil' JIJH 1 l m L'U¡!!IÍ!Í\l' tuoh 1 Nnrma11 IIJII { 1 \\ tlh ~l>i'dll~ I''"JI·t·r t it~s that afl\.·ct in for111at ion prot.'l.'~.,ing. Tht''L' "n.'Jlll'~t'lllitt inn;tl d h'1. h'" an· IH·II d• 11. 11 llll'tlln 1 for navigation tllutdlins I1JX.I. 1111!)¡ ami !111 !llllltt'tkalt'li}.'JlliH•IIII' F. ( 'hll'<lflhtlt .... ~IHI·I, Milll'n.·t al. 1 1 Jll~; Nit'kl~rsun I'IHXI.

Wt~ ¡¡ttt•nd to produt·tion. distrilllllion. tr;m ... uti~~it~n. and uan,fulltl;tllilll ni thl'• hno1\ 1 edgt~ in spL·cili~.· sut·io ~.·ultur¡¡l t'lllllt~\t,. Tltt• implit:atiPII" g11 le~t·~"'HI '".~nuttH· 'lll'f1Vt.'.

addrt•ssin¡! 'lllllt' ol" lht• major nitiqm~.., ol anthmpnl11gtv;d ll'Waltlt, ... udt ·•·· tlt.\11111¡~ 11k.1

systems as units witlmut history.

Categorization and Reasoning 337

Cultuml (.'om·¡•nsus and Residual Analysis

We do nut c.:nnsitkr ~·tllturt• tu h~ a limitcd set of practiccs ami lwlid< hut rath~r th~ distrihution of ideas in a particular group nf ¡woplc. Our intcrcst is precise! y tn lktt•mli 111~ tlw pallt!l'llS reflt~cted in thcsc distrihutínns :111d to cxplain thc proccsses that may lw lwhiml sueh pattcrns. Wc use thc Cultural Consen~u.~ Mmkl (C'CM) to mcasure the existellCl' nf a rnnscnsus alllllll!/. gnntps of partid­pauts amlthc extl'nl 111 which an imtividmtl¡ntrlici­pat~s in this l'llllSl~Hsus nr ap.l't'CS wilh thc overall modd (Nak¡m ami Rllllllll'Y 1 lJX4; Romncy ct ul. 19K6; Ross .:WO·ll. Tlw ('('M is a faetor-analytkal modclthat cxplun~s tht• ~~hscrvl.!d partidpant ugree­mcnt matrí x in ternh ol varíaiiL:t: cxplninl.!d by thc lirst factor. < \ 11\S~Il\lls 1:an be u~sumctl if ( 1) lhe ratio uf 1\rst ami s1:cond f'a~lor ~igcnvalucs is grenter lhan J, (2lthc lirst l'al'hll' l'Xplains nlargc amount of varinnL'l', ami U) a ti partidpanls' lirst raewr loud­ings are high ami pusitívL~.

11' ~:ons,•nsus l'Xists w~: are formully justilicd (1 J lo aggr,•gatl' individual n:sponscs lo a modal rcspons~: l'or •:nmpamt.ivc purpnsrs and (2) to explore th~ cxisli.'lll'l~ nf subgmups of ínfnrmunts, huscd 1111 palll'rn' tlf n•sitltwf agreeme11t-

ngrccment not explained by two individu!lls' par­tidpation in the overall consensus (Nakao md Ronmey 1984; Romney et aL 1986; Ross 2004).

Residual agrcement is calculated by sub­tractíng predicted agreement (the ptoduct of two particípants' individual agreement wíth the consen­smtl model) from obserPed agreement, The tesult­ing residual agreement matrix can be explorcd with respcct to specific group differences (is within-group residual agreement higher than between-group residual agreement?). Distribution of residual agreement does not have to be sym­mctdcal, that is, members of one group míght agrce more with their peers than with. members of the other group but not vice versa (see Medin et al. 2006a for an example). In this case, the first gmup holds a sub-model not shared by themem­bers of the second group, which does not have a group-specific sub-model. Residual analysis also allows us to explore whether specific personal attd­butes predict higher residual agreement. Combined, thesc analyses provide powerful tools to explore the structure and distribution of domain specific

knowledge.

ResL•arL"hers in folkhiology havc bcen on the forefront of integrating di verse the01ies and metilmls. Tmditionuf ethnographic methods merge with experimental field methods and s¡K•eilil' attalytiealteehniqucs, such us the cultural consensus model, the analysis ofresidual

agl\~l~ntenl. ami socialnetwork analysis.

CATEGORIZATION ANO REASONING

'1 'he assumpt ion ora universal folkbiology domain might seem challenged by linguistic d~ta. h11· exampk. most Maya languages do not have words (tho~g~.the~ m~y ~ave gra~mat1cal part kks) for "living kinds," "animals," or "plants." Instead, ¡mtiallmgmsuc encodmg based

· · · · ' 1' · 1 1 ("t · "/"m nmal") This however does not on speeiltt~ wonls huppcns at the híc- 01111 eve tee m · , , . · 1 t al categories that share ¡mpor-mcan thal animals ami p/ants are not recogmzec as concep u · · " "b · · bl t dt' e" or "grow " Many perhaps tant t'catures, umong othcrs "bcmg ahve, emg a e o , . · • most. Indigcnous languages share this. Some languages (includmg Yucatec Maya) mark

"planl" tlll~l "animal" with specilic prelixes or counters. . The hig"csturgument ¡11 favor of a shared domain of folkbt~lo~y ~omes from rese~ch

· ·."' · . · · ··]' , ·"·l'y plat1ts and animals 111 stmJiar ways, suggestmg mto catcgor!l.allon. Pcoplc appem toe t~sst . ' , . .

l. . · t d t ct the "lines and cracks m the evolutlon

that m u· eognitivc apparatlls evo! ve( m ways 0 e e . d . of spc~.:ics ( ;\tran ¡l)l)(), ¡l)l)H; Bcrlin 1992). In this account, folkbwlogy represents a ommn

338 Chapter 20 Cognitive Studies in Ethnobiology

ofhuman cognition that specitically evolvcd tu rcasun ahout and tu intcrm:t with thc biologi­cal world. This would make folkbiology un innutc cognitivc l'aculty, likc languagc (act:ord­ing to sorne theories), nai've physit:s, alHI na'ivc psychulugy. Studics with infants indit:atc thc existence ofinnate and quickly acquircd skclctal principies spccilic to thc ahovc-mcntioned domains. Some researchers hold that, rather than heing an indcpcmknt domain. hiological understandings develop out nf childrcn's umlcrstanding 111' l'ulkpsychology: thc way humans reason about othcr humans. In this acwunt, young dJildrcn initially rcason about animals and plants based on thcir knowlcdgc almut humans allll, only alkr going through a conceptual change (akin to Kuhn's paradigm shirt). do tllL'y dcvclop a truc l'olkbiology (Carey 1985). We will come back to this discussion, as it hcars upon sume crucial issues of child development as well as thc role of culturalallllcxpL'rtisc diiTcrcnL·es.

Interest in taxonomic structures carne in part l'mmlinguistiL· t•vidcnce showing the exist­ence of similar taxonomies around thc glohe (Bcrl in 1 t)92 ). Ex pcrinll'lltal sorting mcthods (see Ross 2004 for some exampb) supportcd ami extended thc linguistic cvitlcncc to a strong body of data describing some cure principies ol' laxonornic structurcs.

The interest in taxonomic structurcs parallelctl thc coguitiw scÍL'tlt't' iutcrcsts in categ­orization and categories as the lmilding /Jiocks o( thought ( Smitil aJHI Mcdin llJH 1 ).

Categories not only allow for cflicicnt thougilt and conllllllniL'at ion hy lurnping clcmcnts together (see D' Andrade 1995), bul also- amlmaylw llliH'l' impmtantly catcgmics ami categorical slrm:tures provide thc bases l'or rcasoning pron•sst•s.

Criticism of anthropologkal w.:cnunts ol' l'olk-taxonomit~s propost•d tlwt thc taxonomi­cal structures do not represen! lndigenous l'orms of thought, hut instcad are tlw outcomc ol' the structuring produccd by the methmls applicd 11 :Jien 1 lJH(, ). To countcr this clainr one needs to show that thc elicited taxonnmit: structurcs art• actually used by nur inl'ormants when reasoning about thc spedcs involvcd. lf this is the L'Hst~. Wt' can assuniL' that the elicitcd stmctures represen! somc aspcct ol' hmv humans organilL' knuwll'dgt•. l ~vidt'lll'L' now cxists that this is the case. Arguing against a utilitarian pcrspt~ctivc, that is, that lndigcnous p~.:ople know the world only to the cxtcnl that thcy need it ( 1 1ianH urd 1 tJ7 2 l. lkrl in pn 1p< 1ses a vicw that accounts for the emergen ce of systems of biological classi lil'ations as tlw rcsult of "human beings' inescapablc amllargcly UIIL'llllscimrs apprcciation uf the inhL'f'L'IIl structurc of biological reality" (Bcrlin llJ92: H). Severa! questions imrm·diatt'ly emerge fm J'urthcr research. First, how do folk-taxomnnics lll' living kimls ~·omparc tll st'icntilic taxl.lllomies and to one anothcr? Second, are folk-t:rxonomks cmployt•d in rl'asonin¡!. stratcgiL'S (ami if so, how)? Third, nre there specilic kvcls in thL~ taxonomks that art• more has k. lúr example, deemed as more relevan! l'or inductivc rcasoning'! hntrth, how dm·~ L'illegorization ami reasoning hold up in a context of cross-cullural and cros.~'"t'\lll'rlist• tl'SL'arch'.'

Categorization: Expertise and Culture

We have comparative data from Europl!an-J\mcril'an lish t~xpel'ts aJHIJH1VÍL't~s from tlw south­east United Statcs (cnst Plorida. wcst r:lorida, Texas. ami North CamlinaJ !Bnstcr and Johnson 1989); cxperts and noviecs on songhirds and tropical frl'shwatl'r tish (.lohnsun and Mervis l9lJ8); freshwater fish cxpt:rts allll noviL'es antong ML'IIolllincc and Euro­Americans in Wisconsin (Medin el al. 2002. :?.OOúl: hin! l~Xpcrts ami novit.'t's in Chit:agu: Itza' Maya of Guatemala (Bailenson el al. 2002 ): Itza · Maya ami lln i vcrsity of M il'lrigan students on local mammals (Lópcz ct al. }lJlJ7), and difkrt~nt kinds (11' tn~c L'Xpcrts in thc greater Chicago arca (Mctlin et al. llJIJ7). In addition \W havt~ data on T1l'ltal M a va l'armers ancl their plant clnssilication (Bcrlin l'l al. 1974 ), as wcll as Aguaruna hin! cla;~ilications

Categorization and Reasoning 339

(Boster et al. 1 986) and how they compare with those of University of Kentucky students (Boster 1987; Boster and D' Andrade 1998).

. S~veral points ~ecorne clear fro~ t~is body ofwork (see also Hunn and Brown, 2011): F¡~·st, ~(~lk-tax<~n.om~es are generally sumlar across the globe and tend to agree strongly with scientihc classificatwns. On average, the correlations between folk-taxonomies and scienti­lic classificatim~s range aroun_d r = 0.6 (see Ross and Tidwell2010). This lends support to the above-mentJOnecl suggestJons that folk classification systems might indeed have devel­oped as the intcrplay of cognitive factors (including perception) with the biological world, rather lhan one or the other. 1 Second, in-group and cross-group agreement are very often coupled with systcmatic within-group differences. Two candidates to account for group differenccs ha ve been tested: cultural fi·ameworks and expertise, both of which have been shown to impact categorization. Boster and Johnson (1989) have shown that the move from novice to expcrt is not justa m ove from not knowing to knowing, or from an incoherent to a more coherent model, but a clifference in models per se. Expe1ts tend to be aware of and pay attention to features not recognized or valued by non-experts.

Following the idea of different goal stmctures and related practices, Douglas Medin and his collaborators explored the categorization schemes of different kinds oftree expetts in the wider Chicago arca (Medin et al. 1997). Results indicate that both agreement and group­specific disagreement are largely explainable with respect to the needs and interests of the groups in question (Medin et al. 1997; Proffitt et al. 2000). Acknowledging expertise as multidimensional opened the spuce of exploring the role of cultural frameworks or epistem­ologies. Along thcse lines Medin and collaborators compared Menominee and Euro­American llsh experts and novices in rural Wisconsin (Medin et al. 2002, 2006b). Given thc setting, "novices" in these studies were rather knowledgeable when compared to college students-the usual suspects in comparative research. Everyone in the arca had done at least some kind of fishing at one point in hisjher Iife. Previous studies· on categorization and reasoning suggested that experts would agree more with one another than with non-experts of their own gro u p. On the other hand, non-experts in these studies were always college stu­dents, who differcd from the experts not only in their lack of expertise, but also in factors such as age, education and incentive to participate (very often class credit).

Members of all four groups basically agreed with one another on the classification of local freshwater fish species. Experts and non-expetts of each group agreed more with one another than with either the two expert or the two non-expert groups. Our data seemcd to ha ve tapped into culturally specific differences in the acquisition of expettise lead­ing to diffcrenccs in kinds of expertise. Data c!early establish the importance of cultural fra­meworks in the acquisition of folkbiological expertise in ways not captured by studies simply looking at levels of expertise.

An extcnsion to the above-mentioned study with Menominee and Majority Culture fish­ing cxperts clarifics how specific cultural frameworks provide the ground for emerging differenccs among experts across cultures (see Medin et al. 2002, 2006b).

Combining the cultural consensus model with an analysis of residual agreement (see Box 20.1) we explored the folk-taxonomic models ofthe two expert groups for lo~al fre~h­water fish (elicitcd in a carel pile sort). We detected a cross-group consensus parred w1th

1¡¡ is importan! Lo note thal different dimensions of how people categorize their ~iological world an: o~en intcrdcpcmlcnt. Whilc pcoplc might attend to different dimensions, the outcome m terrns of categonzatto~ of . living kinds might be similar. For cxample, for Menominee fish ex~~rts (di~cussed below) we ":'ere able t~ 1denttfy ccological reasoning in thcir catcgorization of freshwater fish, en!a!lmg top¡cs su eh as food cham and habita!. Both

of thcsc dimcnsions m-e clcarly linked to thc morphology of fish.

340 Chapter 20 Cognitive Studies in Ethnobiology

systematic asymmetric differences in residual agreement. Menominee experls holu a submo­del not shared with Euro-Americans, but not vice versa. Wc aggregated the data for cach group into a combined model, which was analyzed using multidimensional scaling. In arder to represent the model of the Euro-American experls two dimensions were needed, cor­relating with the desirability of the Hsh ami their size. For the Menomince data three dimen­sions were needed to achieve a Ht for their sorting elata. Two dimensions eorrelated with size and desirability and the third dimension-not found among Euro-Americans-cmrelated with what we termed an ecological dimension (for example, sorting by habitat).

Severa! months Jater we conductcd a set of different but relatcd lasks. First, wc asked participants to describe fish-lish interactions for all possiblc pairs or 21 llsh species (e.g., "Does A affect B or B affect A?"). In this task we asked aboul 420 potenlial relations within approximately 1.5 hours, that is, questions were paced at a f'airly high speed.

We detected the same agreement pattcrn: cross-group consensus with only Menominee holding a systematic sub-model not sharcd by Euro-American experls. Menominee experls reported more relations overall ami more reciproca! relations. Euro-American lishennen mainly reported interactions involving adult llsh of the kind "u musky will eat a northern." These relations were seen by Menominee too, but they added relations hetween lish ol' the whole life cycle as well as relations other than "A eats B." Intereslingly, lherc was only a small set of relations reportee! by Euro-American lish experts hut nol Menominee. These relations typically involved food-chain relations between predalor ami prey lish thal are rarely-if at all-found in thc same waters (a t'acl lhal was lypically menlioned by Menomince participants).

On the surface it would seem that we were observing cultural diiT!.!rence in knowledge. However, ü·om our ethnographic work we knew that the partieipaling Euro-·Americun experts were as knowledgeable as their Menominee counterparts with respecllo lish hahitals ancl it seemed implausible that Euro-American lish experls would have so lillle ecological knowledge.

In a follow-up experiment we had parlicipanls sort the lish according lo di!Terenl habi­tats (each üsh could be assigned to severa! habitats). Members ot' both groups did not diiTer in their responses. Euro-American experts described lish as nol sharing a habilal, l'or which in the previous task they had describcd a hig eats sma/1 relationship. These data rdnt'on:ed the notion that the cultural differences triggered in the t'ormer Las k did not represen! a simple cultural difference with respect to existing ecological knowledge.

Provided the differencc in knowledge organization, we theorized thal the enclllllllered cultural differences might represent differenccs in C/('Ce.\'.1' to knowledge rather titan knoll'!­edge per se. Thc sorting task suggesls thal Mcnominel.! lishermen makc use oran ewlogical organization, which might facilitatc answering questions aboutlish .. Jish interactions. On the other hancl, if thc Euro-American experts focus more on taxonumic relations it may take more time ancl effort to rctricvc infonnation about ecological rl'latiuns. To test this idea we repcatecl the lish- Jish intcraction task severa! monlhs later. llowever, 1 his ti me wc reduccd the number of probes from 420 to 35 (focusing mainly un the probes ror which differences were found in the initial task), allowing for approximately the same time. Results conlirmcd our hypothesis. When providing the parlicipants with more time lo answer the cultural diffcrences disappear with the Euro-Ameril:ans answL:ring likc Menominee, who respond in ways similar to thc l'ast paced lask.

Experts ofthe two groups share base knowlcdgc wilh respecl to ecological rclations allll üsh habitats. This should not be surprising given the fact thal on average experts or the two groups fished for over 40 years. Arguably, knowing whcre lish can he found reprcsenls an important piece of information within llshing, This ecological knowletlgc, however, is nol

Reasoning: Expertise and Culture 341

eq u al~ y accessible. VI_ e find systematic ?roup differences ( which one might be tempted to call cultmal), yet these d1fferences are not m knowledge per se but in access to this knowledge.

Cultural frameworks clearly play an important role with respect to categorization. The data fmther show. t~~t categ~rizations provide an organization of knowledge, which in tum affects the accesstbthty of kinds of specific knowledge.

This resear~h illustrates the importance of a combination of formal quantitative tasks and ethnographJC methods. Data show that it is important to pay attention to the nature of the interview and probes applied. Instead of attempting to find sorne diagnostic "gold stan­dard" task that will reveal what people think or know, one needs coordinated and converging measures across a range of tasks.

REASONING: EXPERTISE ANO CULTURE

Research in the cognitive sciences has shown that category structure provides the basis for reasoning strategies. These are considered heuristics for inference making (or decision making) when relevant information is incomplete. We will focus on two kinds of reasoning. The first is inductive reasoning about categories and their prope1ties (what is often called category-based induction or CBI). Cultural research has shown the importan ce of framework theories and the organization of knowledge to this kind of reasoning. The second is causal reasoning, on which interesting cross-cultural research is also taking place (Burnett and Medin 2008).

Research on the use of categories in reasoning has been guided by theories of induction that suggest pdnciples of induction, which may be universal. Probably the best known theory is the Osherson et al. (1990) similarity-coverage model. Three phenomena associated with the theory have received the most attention: similarity, typicality and diversity.

The similarity principie of induction describes the fact that two kinds seen as similar (closer related in terms of their taxonornic distance) are more likely to share a previously unknown (and invisible) propetty /charactedstic, compared to two kinds that are taxonomi­cally more distant. For example, informants usually judge rnice and rats as more likely to share sorne unknown property than rnice and penguins.

The typicality principie describes the fact that more typical members of a category are more likely to have features common to all the category members than less typical ones. For example, if infmmants are told that sparrows have sorne protein x inside them and that pen­guins have sorne protein y inside them, they judge that it is more Iikely that all birds have protein x than protein y.

Final! y, the diversity principie describes the fact that individuals are usually more Iikely to asciibe a property to the whole category when told that two taxonornically distant category members share that propetty, than when told that two taxonomically similar category mem­bers share a propetty. A projection from mice and cows to all mammals is stronger than a projection from rnice and rats to all mammals.

Studies with undergraduate students have shown stable effects with respect to these three phenomena. However, cross-cultural and cross-expertise studies reveal quite a different picture. Lo pez et al. ( 1997) compared the categorization and CBI of University of Michigan students with Itza' Maya of the tropical rainforest of Guatemala with respect to local mam­mals (for each group a slightly different set of mammals was used). Specifically, they tested (!) whether members of the two groups use a similar taxonornic structure and (2) whether they use the three above-described principies when reasoning about categories and category members. The researchers found that Itza' Maya and Michigan undergraduates tended to sort

l

l ¡

342 Chapter 20 Cognitive Studies in Ethnobiology

rnammals into categories in more or less similar ways, relying on morphologil:al character­istics and, in the case of the ltza', also on ceologil.:al factors such as habita! (c.g., otters are distinct as water creatures and bats are considcred to he hinls by ltza' l. Buth groups also showed similarity and typicality ciTccts in reasoning. Howcver, although undcrgradu­ates relied heavily on thc diversity principies, l!l.a' Maya farmcrs showed lwlow chunc¡•

diversity reasoning. The study has obvious limitations as it confmmds cultural di!Terem:L~s with difti:rences

in age, education, ancl so on ami, most notably, in cxpertise with respccl lo living kinds. 1t does challenge, however, the univcrsality ofat leaslonc oflhL~ principies, clil•asity. Thc chal­lenge then is to understand why the two gruups reasoncd su dillercnlly wlwn il camc to taxo­nomic diversity.

Subsequent studics pinpoint domain knowledgc ami cxpcrtise (hulh thc levl'i ami kind of expertise) as being onc critica! factm. Proflitt et al. (2000) studied inductive reasoning about trees among three different groups of Euro-American trec ex¡K'rts: landscapers, park maintenance workers, and taxonomists. Park workcrs, likc thc Itza' Maya tcsted by l.o¡wz et al. ( 1997), responded reliably bclow chance with I"L~S[k't:t lo the di1·1'1'.1itr flrine'ifl/1'. Another finding is of intercst herc: whcn judging which of 1wo kinds of trecs was more likcly to share a discase with all othcr u·ccs, thc threc dillcn:nt groups uf Chkago·arca tree cxperts preferrcd thc tree with wilkr geographic distrihutitHI or grt~atcr intrin~il" susL"L'P· tibility lo diseasc. In thc formercasc, thc idea is thal trces with widcr gt~ographk distrihution have greater potcntial to pass thc disease In othcr species. In tlw !alter case, thc ralionalc is that the discase will spread mure casily among trees uftlll' susn'¡llihlc spL'L"it•s. which I"L'JHins the disease widely distributcd amlmme likcly to spread to otlll'r spel"ics.

This smt of ccnlogical and causal rcasoning appcms lo IK' pn llllinent aiiJIIIIg i 11 1\lrmant.s with considerable domain knowledgc. In rcasoning ahoul dist~ascs amlt~n;ynlt's tor "littk­things inside") in birds, both North Americ.:an hirdwatchers and ltt:t' Maya rarlliL'I"S in Guatemala tended to base thcir inferenccs on causal cculogical illlL'ntL"tions, '1lten lot·using on geographic dislribution (Bailenson et al. 2002). They lL'Iltbltu [H"l'I\:r, as ¡H·e1niscs, hirds that were rich in known eeologieal assoeiations with uther hinls.

Finally, we asked the Menominee and Euro-American lishenncn of Wisctlllsin t1 • re a~' 111

about diseascs and enzymes in Jish. Mosl ol"the prohL:s lcnt themst'lves lo rca~oninp. by typi cality, similarity, or diversity. Ovcrnll, only I.J% of infercnccs WL'fL' htN~d 1111 ~imilarity ami/ or taxonomic.: rclalionships. Fully ()()IYc, wcrc bascd on translllission of tlw pmpl'rty tlllllllgh ecological intcraetions (Burnett el al. 2005 ).

One might conclude that only noviees··· lacking additional knmvledge us~~ laxunultlit· similarity as a basis for reasoning. The story, howewr, is more l'IHIIpkx. Knuwkll¡•.t•ahil' n·a· soners almost su re! y prefer similarily-hascd stratcgics fm propL·rtiL•s that ( thL'Y hdiL·n· l par· ticipatc in the similarity-based :>lrtH.:ture of thc domain. ProkssinnallaxtHHllllists did shuw divcrsity eiTeets ami cmploy taxonomk similarity most of thl' tiliiL' t l'roflitt t't al. :!OtlOl. Similarity-based slructurc formed pan uf a causal fralllL'Work. Knowkdge providt·s Ikxi bility: a varicty of stralcgies thal allow the n.:asonL'r to prujl'cl difti.•rcrll propcrtit•s in di llncnt ways. Shafto ami Coley (2005) found lhal, whcrcas fishanletl pn•jecll'd dist•ast's avcmdn1p lo food chain relutions among marine animals. thL'Y ¡)J"ojcL·!l·d IIHH"t' ahstract or amhi¡!ll\llls propcrties likc an imaginary "propcrly ealled surca" liiiHlllg tht~ stllllt' animals at·t·onling to similarily or taxonmnic.: relatcdness, as did domain nnviL'cs.

Even novices show this kind of lkxibility when slimuli tap tlll'ir knuwll'd~!l'. llsing l'l"ll logical contmsts that even undergrmluates oftcn knmv (t:.g., jungll' neatun:s wrsus ikSl'il

ercatures), Shafto, Coley, and Baldwin (Shalio el al. 2005¡ 1\lund th;¡t, a¡winst a hal"k¡!l'llUIId prcferenee for reasoning lll'cording to laxonomic rclatcdnL'ss, undt~rgraduatc~ slwwed a

Reasoning: Expertise and Culture 343

ten~lcncy to distinguish be~ween prop~rties. Participants with greater knowledge of the eco­logtcalyroups were more hkely to proJect diseases and toxins, butnot abstract properties Jike "sarca, among eeologically related animals.

Causal stories, howcvcr, are not uni-dimensional, but are often influenced by the fore­grounding/hackgrounding of specific kinds of information. One way to envision this ¡8

Barsalou's. argumcnt of goul-~leri;ect categorization (1991), special ways of categorizing ami rcasonmg thal make certam kmds of knowledge more or less accessible. Cultural dif­fcrences may oflcn be saliency effects driven by framework theories or epistemological oricntations that lcad to diffcrcnt orientations with respect to sorne domain like folkbiology or thc rdation to human being of the rcst of nature (Bang et al. 2007). We will come back to this point.

Categorics might providc a privileged leve! for reasoning. The idea of privileged or h11.1"it' h•t'l'l has been descl'ibed by Rosch et al. (1976), for whom the generic-species leve! provitkll the basic leve] for reasoning. A psychologically prefen-ed rank is inferred that maximizes the strength of any potcntial induction about relevant information. Rosch and col­leagues ( 1 975) were able to show that for artifacts the generic-species leve! (hammer, gnitar) indeed constituted sueh a privileged leve!. However, for biological kinds the privileged leve! moved up to thc lifc form. Forexample, insteacl ofmaple ancl tt·out, Rosch etal. (1976) found that trec amiJish operated as basic-Ievel categories for American college students. Thus, Roscll's hasic leve! for living kinds gcnerally corresponds to the Iife-form leve!, which is superordinate to the generic-species leve!.

In contrnst to Rosch ami colleagucs, Coley et al. (1999) founcl that folk-genetic categorics werc inductivcly privileged for both Itza' people and American undergraduate studcnts, mcaning that both Itza' Maya and undergraduate students knew that inferences l'rmn and to l'olk-gcnerie categories were consistently stronger than inferences from and to n1on.• general eategorics, and no weaker than inferences from and to more specific categories. TogL~ther wil h the data providecl by Rosch, the data indicate that across-culture the genetic species leve! is privileged in that people assume that it cardes most information. Knowing about the im1mrtunce of this leve!, however, is clifferent from knowing the species in volved. While the students studied by Roseh et al. knew about hammers and guitars, they were not familiar with maple trees and trout. Thus Colcy et al. argue that it may be more accurate to charactcrize cultural dit'lerences in terms of the degree to which knowledge and exped­cnL'e l'Orrcspond than as diffcrences in the location of a single privileged leve! (Coley et al. 1999).

Reasoning, Culture and Behavior

Wc llave identilietltwo main reasons to study how and what people think about living kinds. 1-'irst, category-hascd reasoning strategics might provide the building block for agr~ement paltl~rn within (ami to somc extent across) populations, if underlying ~~tegones are sharcd. They allow us to addrcss un importan! puzzle in anthropology: t?e st~b1hty of cultural moti e ls o ver time. Sccond, how people reason about the world has a d1rect unpact how ~hey act u pon the worltl. We admit that much more data are needed to confhm these two pomts. Still, wc think suffieient cvitlencc exists so that further inquiries are warranted. .

Experimental rcsearch can open new insights into ~~~portant processes. Fo.r example, m thc task with lish expcrts from Wisconsin we asked partiCipants about4~0 poss1ble fish-~sh · · · k d It , ' M nd two g¡·oups of 1111grants to the tropical Jntcracttons. In a relatetl stutly we as e zct aya a .

· · · ·1 t t , · 1 plant interactions w1th respect to local nunlorest ot northern Guatema a aJou <tmma- '

344 Chapter 20 Cognitive Studies in Ethnobiology

species (Atran et al. 2002). While we asked approximately HOO questions, wc still nnly cov­ered a fraction of species or species-interactions that actually take place in thc tropical rain­forest. It seems implausible to assume that people would lcarn thcsc irHemctions either through direct observation or through a process of individual instruction ami memnrization.

How then does consensus emerge? Why do people agrce with one another'! Thesc ques­tions address an importan! issuc of anthropological rcsearch: the cnu.:rgerH.:c of agrecmcnt and consensus. They also address the stability of cultural nwdels across generations. We have some evidence that CBI provides one mcchanism through which pcople gerwratc new (explicit) knowledge. In the already mentioncd plant---anirnal intcraction task wc L'om­pared Itza' Maya from two adult generations with n.:spccllo thcir responses. Wc found that young Itza' Maya differed from thcir elders in some responses, yct still agrecd with onc another. This suggested that agreement can emerge in thc absencc of dirct:t ohservation or teaching/learning. Exploring the cases whcre young ltza' Maya agrccd, hut systcrnatically differed from the responses of their elders, it beca me clear that young ltza' Maya use ccrtain animal-plant interactions and extend thc responses lo interactions with similar speeies involved. While on average this might providc a rcasonablc rcsponsL' (as similar animals might affect similar plants in similar ways) we have some cases wherc it doesn't, openin¡! a window into the underlying mcchanic.:s. For exarnple, older lt1.a' Maya makc a dillL•r"L·nce between the way howler monkeys and spidcr monkcys aiTcct lhc rarnon tree. llow lcr nlon­keys help this tree species by swallowing thc en tire sccd ami dispersing it, whereas thc spider monkeys hurt the tree by destroying the seed. Young ltza' Maya, hmwvcr, owrcx lL'tHI si rní­larity across the two monkcy speeies ami attribute thc samc cl'f'ect on the ranHHl tree. Severa! other examples ¡mint in the same direction, supporting thc idea that young lt1.a' imlcL•d use their (shared) taxonomy to generate agrecd (albcit wrong) responses (scc Atran el al. 2002 l. Thus taxonomic knowledge includes tacit or im¡J/icitlowll'lt•dgt• tlwt is availahk lo produce new knowledge when needed. Howcvcr, givcn expertise dil'f'erences as well as ehanges in input conditions at the time of knowlcdgc formation, systematil' diffcreneL'S might he expected (see Ross 2001, 2002a,b for an cxamplc of intcrgencrat ion al changc among thc Lacanclon Maya of Chiapas).

Using the animal-plant interaction task describcd abovc, we wcrc intcrcsted in link in¡! ecological centrality with values and bchavinr. Ecological ccntrality of' a plant was ddined by the number of animals it helped. Plants thal would help many animal.~ wcre rc¡.wnk-tl as more central than plants that would help fcw or no animals. ScvL~ral nHlnths alkr this task wc conducted another set of experiments in which partkipants had lo rank-mder plants aeconl .. ing to thcir importance. Three dil'ferent sccnurios wcrc ollercd: ( 1) imporlaflL'C to Ego: ( 2 l importance to Gocl; ami (3) importance lo the l//'11.\', tril'kster-likc rores{ spirits who [lf'O[L'C[ the forest. Ego values ami valucs according to God cmrclutcd strongly with thc utilitarian value of plants (construction, medicinal, f()()d etc.), as "CJod watchcs out lúr his childrt·n." Thc rank-orcler l~ll' the arux correlated with thc above .. descrihcd ccolo"ÍL'td Cl'fllralitv

{"" ~

index, indicating that in the cycs ofthe Itza' the arux actual! y protect thc spccies that are CL'fl· tral to the survival and wellbeing of the animals-··-rwt the humans! This makcs dcar that once we factor out utilitarian valucs, dominan! in a socicty whcrc searcity of' rcsources is endemic, ltza' Maya clearly have an agrccd-upon notion of ecologil'al ccntrality ol' s1weics. Parallel to these cognitive stuclies wc conductcd lr(~e counts in dil'll.•rcnt plots o!' thc threc groups that participated in the overall study (lt:w' Maya, as wcll as two migrant groups ¡ ami found that ecological centrality predictcd Lhc l'requency of' trces found in tlwse plots l~1r ltza' Maya only. This indicatcs that Itza' Maya not only know about th~~ l'crmalitv of specitic species, but actually protect these spccics ami changc thc cnvironmcnt aL·eurdi;1gly (see Atran et al. 2002).

Reasoning: Expertise and Culture 345

We. could not .come np with a similar behavioral measure for our study among Menommee and Euro-Amencan fishermen. However, we were able to explore the role of stereo.types people hold about members of the other group, both with respect to fishermen (Medm et al. 2?06b) and to hunters (Ross et al. 2007). Most of the stereotypes were held by Eur~-Amencan hunters and fishermen and directed against Menominee (although ~en~mmee also. h~ld s?me stereotypes about Euro-Americans). In this study we probed Wlthm-group vu_natwns m ~rder to better understand more specific aspects of stereotyping. !l:e E~ro-Amencans who d1ffered most from Menominee experts' goals or ways of categor­¡zmg f1~h showed more stereotyping than their peers, who tended to agree more with Menommee on these matters. Initíally, we thought that this might be an outcome of famili­arity with individual Menominee, but social network data proved that this was not the case. Apparently, observations are interpreted and evaluated through the culturallens ofthe obser­ver. For example, a Euro-American hunter might see Menominee killing smaller bucks than he himself would shoot, given his focus on trophy huntíng. This "bad behavior," taken together with the observation that there are fewer deer on the reservation (a fact that is due to the lower ca!1'ying capacity of forests in general), might lead him to interpret Menominee hunting behavior as detrimental to the deer population (see Ross et al. 2007). Clearly then, cognitive models inform human behavior, fueling an already existing conflict about natural resources (see Medin et al. 2006a).

Acquisition of Folkbiological Models: lnnate Models and Cultural Knowledge

We ha ve mentioned the work of Susan Carey, who ascribed the development of folkbiolo­gical thought to a later stage basically emerging as a conceptual change out of the presum­ably innate folkpsychology (Carey 1985). The core of her finding is based on an inductive reasoning task where children in her sample were more likely to ascribe attributes from humans to animals than vice versa. Carey took this asymmetry as an indication that young children (age < 10) use humans as a basis to reason about animals, for example, that folkpsychology provides the framework for a developing folkbiology. However, for anyone familiar with rural children around the world (including the USA), the urban children participants' ignorance of basic biological facts is remarkable. The participants were all urban children of Boston. We have discussed the role of expertise and the differences in cat­egorization and reasoning between adult experts and novices. Such differences could influ­ence child development. The trajectory described by Carey may describe only the development of novice children with little or no exposure to the natural world. Kayoko Inagaki ( 1990) has shown that kindergarten children (age < 5) raising goldfish, besides acquiring more factual knowledge about goldfish, also attained conceptual knowledge through which they could reasonably predict goldfish behaviormore accurately than children who were not raising goldfish. Moreover, goldfish-raising children were able to predict reac­tions of unfamiliar aquatic animals, such as frogs, using their knowledge about goldfish as an analogy.

We conducted a study comparing both rural Euro-American and Menominee children from Wisconsin with children residing in Boston (Ross et al. 2003). Using essentially the same methods as Carey, we found two interesting results. First, rural children do not show the same human-animal asymmetry as described by Carey for the Boston children. As before, our Boston children show a remarkable lack of folkbiological knowledge­they were at chance on whether trout are alive or not. Second, Menorninee and only they

346 Chapter 20 Cognitive Studies in Ethnobiology

showed clear examples of ecological reasoning (bee stings the bear, the bear eats honey) leading to inferences from one species to another. This finding is especially striking as it par­allels our findings with respect to expetts of the same two communities.

Knowledge elicited in our studies may be transmitted by explicit teaching, yet this is only one possibility. Bang et al. (2007) asked Menominee and Euro-American children and adults about the nature and frequency of their outdoor practices. They found that Euro-Americans were much more likely to engage in practices in which nature is back­grounded (e.g., playing baseball), and much less likely to engage in practices in which nature is foregrounded (e.g., beny picking). There is independent evidence that what we might call "psychological distance" affects cognitive processing in a variety of ways, includ­ing inferences and attributions (see Trape et al. 2007).

A related set of observations comes from Unsworth (Undated manuscript). She asked Euro-American and Menominee adults to describe the last encounter they had had with a deer. In addition to the content of the stories she also recorded the gestures used. The two groups did not differ in the overall likelihood of using gesture, but they showed a vety large effect of perspective when gesturing about deer. Euro-American adults would "place" the deer in some location (using their hands) but a significant proportion of Menominee adults "became" the deer in gesture. They were reliably more likely to take the deer's perspective in gesture than were Euro-American adults. More research is needed, but results so far indicate that this line of research will pro ve fruitful.

Direct leaming is important in knowledge acquisition and severa! studies have been dedicated to this issue (see Ross 2002a,b, 2004; Shenton and Ross, undated; Stross 1973; Zarger 2002a,b; Zarger and Stepp 2004). Most of these studies have explored relations between activities and cultural change (see also Nabhan and St. Antaine 1993). We urge researchers to explore the effects that come with a decrease in expertise and the resulting lirnitations in the power of generating cultural knowledge (see Atran and Medin 2008; Atran et al. 2004; Shenton and Ross, undated). Knowing or not-knowing the name of a species should not be the endpoint of our inquiry but a starting point. (See Wolff et al. 1999 for an interesting study on changes in the specificity of plant knowledge in England based on a cross-time study using the online OED.) Research linking sophisticated cansen­sus theory and social network analysis could explore channels of information jlow, content of information, its impact on the individual mind, and cognitive processing.

WHAT IS CULTURE ANO HOW DO WE STUDV IT?

We have talked much about culture and feel it is now time to say a little more about what we mean by it.

In our view, culture comprises both mental and public representations such as material productions, speech, and other aspects ofbehavior in particular ecological contexts (see Ross 2004; Sperber 1996). What we refer to as culture or cultural concepts are those represen­tations that are relatively stable and systematically distrlbuted in a population (Atran et al. 2005; Ross 2004; Ross and Medin, submitted). We see cultural processes as outcomes of the complex interaction of individual cognitive processes interacting with each other and with their social environment.

First, we avoid cross-cultural studies where "culture" is treated as an independent vari­able, which is inherently circular unless the notion is unpacked into a series of ctimensions or values that could in principie be manipulated. In this case, however, the notion of culture

lf

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Rcfcrences 347

lwl'tllllt'~· l'lliJll.\ and ,·;u¡ lw dis~·ankd. C'ulling diffcrcnees "cultural" does not add to undei\t a m 1 i 111 •.

Sn·•tml. adtlptill¡~ thi~ ¡wrspc~·tiw flm.:cs us lo pcreeive cognitive processes as situated or l'lnl•ntftt'•imam/t'lftllú•n.l !llll~lltal attivitics rdcvanl toan individual's life). They tnke pJ¡¡n: w11hín .1 '•P~'•'tllv ~~~~·i;tl and phy~i<.:al context. Consequcntly, it reinforces a research ~Matl'n ot •'\anunin¡• vt~¡•nitit~n in rdcvant contexts. ft may he useful for some pmposes 111 study ~~~.~~nitiPn in hi¡!lily artilil'ial contexts, but only with an eye toward real-world idt'\ :llh '('.

Thitd. tlw. vívw 111 niltull' illuminatcs thc intcraction ofcognitive and social processes. < 'ultmal vhan¡~~· ímuln•s l.'llfll'l~ptual dmnge (within and across individuals) as well as cha11gc•. i 11 r ltl' ( 1 i ,¡ rihtH ion ( ,f .'i(K'cilic wnccpts within populations. To the extent that the for­mati''" ami IJ¡IIhftli~sit 111 of' t~Oill~epts dc¡ll~nds on thc llux of inlbnnation, it is imp01tant to widt'll um a11alysis pf ín/il!'llltllinn to any kind of information input or cultural practice, a1HI1H H ¡, lt'll\ ~.<1kly <Htexplkit propn.~il ionnl con ten t. We focus on populations, and the dis­ll ihut iun 'ti rqHl''>t'lltat Ítllls anH 1llg populutions, with the goal of expJaining patterns of agree­tm'llt <llld di-.a,!~lt't'llll'llt. 1t is importan! to explain both cultural stabílityjresíliency and niltlllctl l'lttmgt' t!~o.~~ l'l iil., suhmillcd).

h 1\llth aud 1 inally. vbvíng culture as a distribution o !'ideas and practices avoids essen­ti;dilill.l'. \.·ullu1v ur dl'líning itonly in tcnns of consensus or agreement. Instead oftreating disa¡•rc't'lllcnt a.\ thc l'ailun: to timn or mnintain a consensus, it becomes central to our dis­trihutiunal ap¡ll'll:idl (it is signnl, not noisc). However, cultural differences with respect to call'J'.Il!Ítatíon are in tlwmsdves a cause for further cultural differences.

CONClUSION

This hrim~s us hnL'k to thc qucstion: Is folkbiology a discrete domain? The correct answer ~•hould p;·obahly he "yl!s and no." Cognitive scientists ~eem ~o come to terms :Vi~ the idt~a that folkbiology is fünncd around sorne potentl!llly .~~nate sk~Ietal ~nnc1ples. llowewr. f(,lkhiology also scems to be connected to folk-medrc~n.e, by vutue of concepts sul'l1 as

11(¡1•1., dt•ttlfl, und sick, und by the thousa.nd~ of medtcma~ plant~ documented

around thc world. Exploring such common ~round wrlll1~ely produce mcreasmgly complex <K\.·ounts of' how cultural belicJ:~ and cognitive structure mteract.

REFERENCES

AII<\N S. Th,, nwnitiw Jilundatiuns of natuml hi8tory: loW;IId•. un ;u;l·luo¡mlo!(y of' scicncc. New York:

t'anthrid¡~L' t lnivcrsity l'rcss; 1990. . Aiii.\N S. ¡:ulk hiology nnd 1hc authropnlogy ofsc¡cnce.: cog:

niliw uuiwrsals and ~ultuml particulars. Bchav Bnun ScJ

l'l'!H;21 ::'i47 ll01J . . , on-1\Tu,,N S, MwiN PI .. Thc nativc mmd und lhc cultural e

. . ll 1. (M.Al' MIT Press· 2008. slnlclwu ol nwur~~. os DJJ · • ' E ' EU

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