Croft 2008 EvolutionaryLinguistics

ANRV355-AN37-13 ARI 14 August 2008 11:11

Evolutionary LinguisticsWilliam CroftDepartment of Linguistics, University of New Mexico, Albuquerque, New Mexico 87131;email: [email protected]

Annu. Rev. Anthropol. 2008. 37:219–34

First published online as a Review in Advance onJune 17, 2008

The Annual Review of Anthropology is online atanthro.annualreviews.org

This article’s doi:10.1146/annurev.anthro.37.081407.085156

Copyright c© 2008 by Annual Reviews.All rights reserved

0084-6570/08/1021-0219$20.00

Key Words

replicator, selection, phylogeny, comparative method

AbstractBoth qualitative concepts and quantitative methods from evolutionarybiology have been applied to linguistics. Many linguists have noted thesimilarity between biological evolution and language change, but usuallyhave employed only selective analogies or metaphors. The developmentof generalized theories of evolutionary change (Dawkins and Hull) hasspawned models of language change on the basis of such generalizedtheories. These models have led to the positing of new mechanisms oflanguage change and new types of selection that may not have biolog-ical parallels. Quantitative methods have been applied to questions oflanguage phylogeny in the past decade. Research has focused on widelyaccepted families with cognates already established by the comparativemethod (Indo-European, Bantu, Austronesian). Increasingly sophisti-cated phylogeny reconstruction models have been applied to these fam-ilies to resolve questions of subgrouping, contact, and migration. Littleprogress has been made so far in analyzing sound correspondences inthe cognates themselves.

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Phylogeny: a graphstructure, usually atree, representing theevolutionary history ofa set of individuals(organisms, species,languages)

Selection: the processby which theinteraction of theinteractor with itsenvironment causesdifferential replicationof the relevantreplicators

INTRODUCTION

Evolutionary models have come to be employedin several areas of the study of language inthe past two decades. The use of evolutionarymodels is naturally found in historical linguis-tics and also in the study of the origins of lan-guage. In the latter case, however, the employ-ment of evolutionary models is handicappedby the absence of data regarding the transitionfrom our primate ancestors to the emergence ofmodern human language, which is found in allsocieties. All that we can go by is the archaeo-logical record and the comparison of the social-cognitive abilities and communication systemsof humans and other animals, particularlynonhuman primates. Because the study of theorigin of human language does not depend onlinguistic data, it is not discussed in this article.Even so, the area under review is vast andgrowing, and therefore this review is restrictedto research in which qualitative concepts andquantitative methods from evolutionary bi-ology have been applied to the analysis oflanguage, in particular language change andlanguage phylogeny.

EVOLUTIONARY THEORYAND THEORIES OFLANGUAGE CHANGE

In historical linguistics, the parallels betweenbiological and linguistic evolution have beenobserved since Darwin himself first took notice(for a historical survey, see Atkinson & Gray2005). However, the differences in the domainsof biology and language appear to have out-weighed the similarities, and Darwinian evo-lutionary theory has developed over time. Inthe meantime, the advent of structuralism andgenerative grammar has led to the dominanceof an ahistorical approach to the study oflanguage (Croft 2002). As a consequence, lin-guistics has rarely used models from evolution-ary biology. Nevertheless, the similarities be-tween the two have led historical linguists toemploy evolutionary analogies or metaphors.Analogies/metaphors indicate similarities be-tween the two domains (biological evolution

and language change) but do not imply an over-arching generalized theory.

An isolated analogy from evolutionary biol-ogy that has proven to be useful in explaininglanguage change is Lass’s application of exap-tation to historical linguistic phenomena (Lass1990). Exaptation in biology is the employmentof a phylogenetic trait for a function differentfrom the one for which it was originally adapted;Lass slightly changes the definition to apply tolinguistic structures that have lost their func-tion but have come to be employed for anotherfunction.

A recent example of the employment of abiological metaphor is Blevins’s theory of evo-lutionary phonology (Blevins 2004). Evolution-ary phonology proposes to account for syn-chronic phonological patterns as the result ofphonetically motivated changes in the transmis-sion of sound systems from adult to child overtime. It uses the notions of inheritance (via thechild learning the adults’ language), variationgenerated by “errors” in replication (mecha-nisms by which the listener alters what he hearsfrom the speaker), and natural selection (cer-tain sound changes are more/less likely in par-ticular phonetic contexts). However, because ofdisanalogies between biological evolution andlanguage change, Blevins explicitly rejects anevolutionary approach to sound change that ismore than metaphorical.

Although analogies or metaphors betweenbiological evolution and language change canbe fruitful, one does not know which parallelsbetween the two domains are legitimate to drawand which are not, or even more important,which parallel structures must be present forthe analogy/metaphor to make sense. In partic-ular, it is common to assume that the mech-anisms that cause variation and selection inbiological evolution must be the same in otherdomains such as language change, yet the mech-anisms are domain specific. What is requiredis a generalized theory of evolutionary changethat subsumes biological evolution, languagechange, and other phenomena of evolutionarychange such as cultural evolution. Researchershave derived models of cultural evolution from

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biological evolution (Boyd & Richerson 1985,Cavalli-Sforza & Feldman 1981, Durham 1991,Richerson & Boyd 2005). But the generalizedtheories of evolutionary change that have at-tracted the most attention in historical linguis-tics are those developed by Dawkins (1989,1982) and Hull (1988, 2001).

The most crucial feature of a generalizedtheory of evolutionary change is that evolution-ary change is change by replication, a processby which some entity is copied in such a waythat most or all of the structure of the replicateis the same as that of the original. The replica-tion process is cumulative and iterative, lead-ing to lineages. Second, evolutionary changeis a two-step process: the generation of varia-tion in the replication process, and the selectionof variants via some mechanism. Dawkins’ andHull’s models have these properties, as do themodels of cultural evolution mentioned above.In the context of language change, Lass notesthat these properties are necessary to under-stand languages as historical entities (Lass 1997,pp. 109–11), although he does not develop a de-tailed theory of language change on this basis(see also Nettle 1999, Wedel 2006). Evolution-ary theory also rejects any notion of progress.

Dawkins’ and Hull’s models are related butdiffer in important respects. Dawkins gener-alizes the concept of a gene as a replicator.The replicator possesses a structure that canbe copied. Variation occurs through the copy-ing process. Dawkins also generalizes the con-cept of an organism as a vehicle. For Dawkins,a vehicle has been constructed by the replicatorto aid in its replication. Selection is differentialreplication, but for Dawkins it is focused on thereplicator (the selfish gene concept), whereasin more standard neo-Darwinian models, se-lection is a function of the organism/vehicle.

Dawkins proposed that there are units ofculture with heritable structure that replicate;he called them memes and proposed a scienceof memetics to study them. Memes have beeninterpreted as cognitive entities in the minds ofhumans, instances of human behavior, or ar-tifacts. Most memeticists, including Dawkinshimself, assume memes to be cognitive enti-

Replicator: an entitythat is copied andpreserves most of itsstructure in copying

Meme: a culturalreplicator

Interactor: an entitythat interacts with itsenvironment in such away as to causedifferential replicationof the relevantreplicators

ties. Hence concepts are replicators and mindsor brains of individuals are vehicles. Memeti-cists generally use a parasite-host model for therelationship between memes/concepts and themind or brain of the possessor: Memes are para-sites that use the brain (the host) as their vehiclefor replication.

The most extended analysis of languagechange in Dawkinsian memetic terms is by Ritt(2004). Ritt, a historical phonologist, focuses onphonological change. Following Dawkins, lin-guistic memes are concepts in the mind; specif-ically, they are some type of replicable brainstructure. Ritt argues that phonemes, mor-phemes, phonotactic patterns, metrical feet,and phonological rules, or more preciselytheir conceptual representations, are memes.However, linguistic signs (form-meaning pair-ings) are not replicators because, in Ritt’s view,they do not preserve enough structure in repli-cation. Instead, signs are the result of an allianceof replicators.

In the Dawkinsian model, the linguistic be-havior that a speaker produces on the basis ofher conceptual memes exists for the purposeof replicating the memes, not for communi-cation (Ritt 2004, p. 231); this is the selfishgene/meme theory. The replicators are repli-cated across speakers by an imitation process(see Blackmore 1999); variation is generated inimperfect imitation. Ritt proposes several selec-tional pressures for differential replication (i.e.,selection), all operating in the mind/brain. Hefocuses his attention on meme coadaptation as aselectional pressure, using it to account for theinteraction between foot structure and vowelchanges in the history of English.

Hull adopts Dawkins’ concept of replicatorbut generalizes the role of the organism to aninteractor and defines an interactor as any en-tity that interacts with the environment so as tocause differential replication (that is, selection)of the relevant replicators. Thus, the interac-tor’s interaction with the environment is thelocus of selection; it is not a mere vehicle forthe replication of the replicator, and Hull doesnot advocate the selfish gene/meme interpreta-tion that negates the role of the interactor in

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Lingueme: alinguistic replicator,that is, a token oflinguistic structureproduced in anutterance

evolution. Hull argues that interactors may ex-ist at different levels in the biological hierarchy(gene, cell, organism, even a species), althoughthe organism’s interaction with its environmentin natural selection is the canonical case. Hull’sgeneral analysis of selection is thus centered onthe processes by which the interactor’s interac-tion with its environment causes the differentialreplication of replicators.

Hull (1988, 2001) presents a theory of con-ceptual change in science in which scientificconcepts are replicators and the scientists areinteractors. Hull’s general analysis of selectiondoes not assume any specific causal relation-ship from replicator to interactor, so there isno need to invoke a parasite-host model forthe concept-scientist relation. However, sci-entists must be able to cause the differen-tial replication of their ideas/concepts, whichthey do through publishing, lecturing, andteaching.

The most detailed application of Hull’s gen-eral analysis of selection to language change isin Croft (2000, 2002, 2006). Croft argues fora model in which the linguistic replicators arebehaviors, that is, tokens of linguistic structuresin utterances produced by speakers. Croft coinsthe term lingueme to describe the linguisticreplicator. The speakers themselves are inter-actors. The speaker replicates the replicators inspeaking, generating variation in the produc-tion and comprehesion of utterances. In Croft’smodel, linguistic structures evolve via languageuse, not via language acquisition.

Croft’s model, like Hull’s, does not spec-ify the mechanisms by which variation is gen-erated. Croft, like all evolutionary biologistsand most historical linguists, rejects teleologicalmechanisms. Croft allows for widely proposedintentional mechanisms, such as expressivenessand avoidance of misunderstanding. Croft alsoproposes nonintentional mechanisms inspiredby theories of sound change, in which speakersor listeners attempt to conform to conventionbut fail to do so. Speakers are highly variablein the phonetic realization of phonemes (soundlinguemes), as noted in much recent phonetic

research (e.g., Bybee 2001, Pierrehumbert2001) and in the verbalization of meaning ingrammatical structures (Croft 2008). Listen-ers are faced with the problem of analyzingthe phonemes in an utterance from a complexacoustical signal, and they may reanalyze themapping between the phonetic signal andthe phonological structure, in processes Ohala(2003) calls hypocorrection and hypercorrec-tion. Listeners are also faced with the prob-lem of analyzing the semantic contributionof words, morphemes, and constructions froma complex communicative situation, and theymay reanalyze the mapping between form andmeaning in those units via different types ofform-function reanalysis (Croft 2000, chapters4–5).

The speaker as interactor is also the locusof selection: The speaker selects a variant toproduce. In this respect, Croft’s evolutionarymodel agrees with theories of the propagationof change (selection of variants) developed insociohistorical linguistics. In the latter theories,investigators propose that various social factorsassociated with particular sociolinguistic vari-ants in speech communities lead to the propaga-tion (or extinction) of variants, although otherfactors including the social network structureand the frequency of exposure to variants alsoplay a role. Croft argues that functional pres-sures operate only in the generation of varia-tion, not in selection; others take the view thatfunctional pressures operate in selection (e.g.,Nettle 1999, pp. 30–35).

Some of these models have led to mathe-matical formalizations and simulations. Nettle(1999) simulates a model in which languagechange occurs via child language acquisitionand argues that the rate of fixation is pro-portional to the number of speakers in thespeech community. Wedel (2006) presents ausage/exemplar-based evolutionary model ofsound change, including simulations of inheri-tance and selection. The work by Baxter et al.(2006) is a formalization of Croft’s theory in astatistical physics framework (see also Blythe &McKane 2007).

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The model developed in Baxter et al. (2006)shows that some types of selection mechanismsin language change (and other types of culturalevolution) may not exist as such in biologicalevolution. The classic selection mechanism is atype of replicator selection, that is, differentialweighting of replicator variants (their fitness);in language change this is found in the differen-tial social valuation of variants (compare Nettle1999, pp. 29–30). In neutral evolution (geneticdrift, not the same as linguistic drift), ran-dom fluctuations lead to change (Nettle 1999,pp. 16–17); these correspond to frequency ef-fects in language change. In addition to thesetwo mechanisms, there is neutral interactor se-lection, by which differences in the frequencyof interaction with other interactors lead to dif-ferential replication. Neutral interactor selec-tion corresponds to social network structure ef-fects in language change (Milroy 1987); sexualselection may be an instance of neutral inter-actor selection in biological evolution. Finally,the model includes weighted interactor selec-tion, in which differential weighting of the in-teractors with whom one interacts, independentof frequency of interaction, leads to differen-tial replication. Weighted interactor selectionis exemplified in the differential social valua-tion of different speakers; there is no obviousequivalent in biological evolution. Baxter et al.(2008) use their model and simulations basedon it to argue that the New Zealand Englishvariety could not have emerged by neutral evo-lution and neutral interactor selection alone.

Mufwene (2001, 2005) developed an evolu-tionary model for language change that is sim-ilar to Croft’s. Mufwene focuses on two aspectsof the evolutionary framework not discussedabove. First, a language forms a population inthe same way that a species does. Mufwenetreats a language as a species, specifically a pop-ulation of linguistic structures that exist in theminds of speakers in communities, because lan-guages are variable, and their spread, extinction,and rates of change are dependent on speakerpopulations and not on the linguistic system perse. Mufwene follows the parasite-host model

for the relationship between a language andits speakers, but his focus is different from thememeticists. The memeticists argue that thelinguistic concept (the parasite) uses the speaker(its host) to replicate itself, whereas Mufweneargues that the survival, spread, or extinction ofa language is dependent on the survival, spread,or extinction of its host speakers.

The second aspect of evolution thatMufwene exploits is ecology. Languages, andthe speakers on which they are dependent, areembedded in an environment, in particular asocial environment but also the internal envi-ronment of the society and the linguistic va-rieties found in it. Mufwene uses his frame-work to analyze the development of creoles andthe relationship between creoles and “normal”linguistic transmission. Mufwene argues thatcreoles emerge from the linguistic varietiesavailable in the earliest stages of colonization,which in the case of European language–basedcreoles involve nonstandard varieties of the Eu-ropean language(s) and also nonnative Euro-pean speakers (e.g., Irish nonnative speakers ofEnglish, Breton nonnative speakers of French)as well as nonnative speakers of African origin(as in American slave plantations) or indige-nous nonnative speakers (as in the Pacific). Theemerging creole is a result of natural selection oflinguistic structures determined by the ecologyof the social and economic situations of the earlycolonies. Mufwene argues that the emergenceof creoles is not different in kind from “nor-mal” language change, but only in degree—thesame ecological model fits the development ofthe Romance languages from Vulgar Latin, forinstance.

The emergence of theories of languagechange based on a generalized theory of evolu-tionary change is quite recent. Less systematicadaptations of evolutionary concepts in theo-ries of language change continue to be madeas well. Evolutionary, usage-based theories oflanguage change are the strongest competitorsto the innate-grammar, child-based theories oflanguage change put forward by followers ofChomsky such as Lightfoot (2006).


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Comparativemethod: thetraditional historicallinguistic method bywhich soundcorrespondences arefound among cognatesand a protolanguage isreconstructed

Cognate set:corresponding wordsin a set of languagesthat are presumed tohave a commonancestor

Soundcorrespondence: asystematiccorrespondence ofsounds in the words ina cognate set

PHYLOGENYRECONSTRUCTIONAND GENETIC LINGUISTICSA major potential application of more practicalmethods from evolutionary biology to histori-cal linguistics is in the area of genetic linguistics,in particular the establishment of language fam-ilies and their subgroupings. This task paral-lels what evolutionary biologists call phylogenyreconstruction, the reconstruction of thepresumed historical branching of ancestral pop-ulations into contemporary populations, ofeither species or smaller biological groups.Phylogeny reconstruction is accomplished bycomparing phenotypic traits of organisms, par-ticularly proteins, or sequences of nucleotidesin mitochondrial or nuclear DNA. Break-throughs in DNA sequencing and the devel-opment of mathematical algorithms and com-puting power to execute those algorithms haveled to an explosion of research in phylogeny re-construction, of which the most famous result isthe African Eve hypothesis: that all humans arebelieved to be descended from an ancestralpopulation in Africa some 100,000–150,000years ago (Cann et al. 1987, Vigilant et al.1991).

The connection between phylogeny andlanguage history was made in a paper byCavalli-Sforza et al. (1988), which attracted atremendous amount of attention but whose lin-guistic assumptions were rejected by most lin-guists. Cavalli-Sforza et al. produce a phylogenyof human populations and compare it with aphylogeny of linguistic populations, that is, themajor language families in the world. Theynote a high degree of congruence of the twophylogenies, suggesting that language spreadand diversification have occurred primarily viamigration and splitting of speech communi-ties, at least in prehistory. Much of the contro-versy among linguists is due to the authors’ useof language families such as Amerind, Eurasi-atic/Nostratic, Altaic, Na-Dene, Austric, andIndo-Pacific, which are not generally acceptedamong historical lingusts.

One crucial difference between the biolog-ical and linguistic data in Cavalli-Sforza et al.

is that the biological data have been analyzedquantitatively whereas the linguistic data havenot. Since that time an increasing number of re-searchers have attempted to apply quantitativetechniques to the problem of language fami-lies and have made other attempts to relate lan-guage diversification to prehistoric demogra-phy. The remainder of this review focuses onquantitative methods from evolutionary biol-ogy applied to comparative historical (genetic)linguistics; owing to topic and length con-siderations, quantitative methods from otherfields are not discussed nor is research on therelationship between prehistoric demographyand language families derived by traditionallinguistic method.

The Comparative Methodand Phylogeny Reconstruction

The comparative method is excellently sum-marized in the following passage from Ross &Durie (1996, p. 7):

The comparative method (in its strict sense)can be summarized as a set of instructions:

1. Determine on the strength of diagnosticevidence that a set of languages are genet-ically related, that is, that they constitutea “family.”

2. Collect putative cognate sets for the fam-ily (both morphological paradigms andlexical items).

3. Work out the sound correspondencesfrom the cognate sets, putting “irregular”cognate sets on one side.

4. Reconstruct the protolanguage of thefamily as follows:a. Reconstruct the protophonology from

the sound correspondences worked outin [step] 3, using conventional wis-dom regarding the directions of soundchanges.

b. Reconstruct protomorphemes (bothmorphological paradigms and lexicalitems) from the cognate sets collectedin [step] 2, using the protophonologyreconstructed in [step] 4a.

5. Establish innovations (phonologi-cal, lexical, semantic, morphological,

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morphosyntactic) shared by groups oflanguages within the family relative tothe reconstructed protolanguage.

6. Tabulate the innovations established in[step] 5 to arrive at an internal classifi-cation of the family, a “family tree.”

7. Construct an etymological dictionary,tracing borrowings, semantic change, andso forth, for the lexicon of the family (orof one language of the family).

Ross & Durie note that the steps in this pro-cess are iterated because they are clearly inter-related. For example, what counts as an inno-vation in sound change in a daughter languageor languages depends on what is reconstructedas a protophoneme.

Major similarities exist between the com-parative method and phylogeny reconstruc-tion (Greenberg 1992 gives a detailed com-parison; see also Lass 1997, chapters 3–4).First, the differentiation of languages and thedifferentiation of species are assumed to belargely treelike. Nevertheless, both biologistsand linguists allow for the possibility of reticu-lation in phylogenetic trees, certainly for closelyrelated species (hybridization) and languages(dialect mixture). Second, both biologists andhistorical linguists recognize the important di-agnostic value of shared innovations (see steps5–6 above). These fundamental similaritiesmean that the tree-building algorithms devel-oped for biological phylogenies are built onthe same principles as is historical linguisticsand therefore should be applicable to recon-structing linguistic family trees, or languagephylogenies.

A major difference between the two do-mains, however, is that in language, soundchange leads the divergence of the phono-logical forms of words even though they arecognate. Cognate forms are not identical. Ingenetic comparison, “cognate” sequences ofnucleotides are identical. One consequenceof this difference is that almost all applicationsof phylogeny reconstruction algorithms frombiology to historical linguistics have used as theinput data (character traits) to the phylogeny re-

construction algorithm only lists of establishedcognates in accepted language families becausecognates can be treated as identical. That is, thefamily tree (the subgrouping) is reconstructedon the basis of the presence versus absence ofcognate forms for particular meanings in par-ticular daughter languages. This approach rep-resents a signficant loss of information, butmany important issues in historical linguisticscan nevertheless be placed in an evolutionaryperspective even in this approach.

Some techniques from evolutionary biologyare beginning to the applied to the prob-lem of sound correspondence. In particular,techniques from DNA sequencing have beenapplied to the alignment problem. This is aproblem rarely touched on in textbooks on thecomparative method: aligning two forms toidentify the corresponding sounds. This tech-nique is not straightforward because phonemesmay be inserted (epenthesis), deleted, merged,or transposed (metathesis); also, many wordscontain fossilized affixes that do not corre-spond with anything in their cognates in theother languages. Computational linguists haveaddressed the alignment problem for historicalcomparison, using techniques also found inbiology (Covington 1996, 1998; Kessler 1995;Kondrak 2002, 2003; Nerbonne & Heeringa1997; Oakes 2000). This research is basedon minimizing edit distance (Levenshteindistance) between the strings being aligned.Kondrak notes that biologists are beginningto use probabilistic models such as HiddenMarkov models and suggests this as a possiblenew technique to use in historical linguistics(Kondrak 2002, p. 23). Nevertheless, math-ematical formalization of the identificationof sound correspondences is presently in itsinfancy.

Mathematical Techniquesfrom Biology

A wide array of techniques from phylogenyreconstruction in biology have been appliedto historical linguistics, even given the limita-tion to cognate judgments that exists only in


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established language families. This review cangive only a broad qualitative description of someof the methods; the mathematics of the meth-ods is described in various references (see alsoMcMahon & McMahon 2003, 2006 for discus-sion of the methods from a comparative histor-ical linguistics perspective).

Given a set of data such as cognate judg-ments among a set of genetically related lan-guages, two common ways are used to constructphylogenies. Distance-based methods use anoverall pairwise distance measurement betweentwo languages. Historical linguistics has alreadyused a distance-based method to measure theproportion of shared cognates: the lexicosta-tistical method. (Lexicostatistics has also beenused when similar word forms are not knownto be cognate; here we discuss only assumedcognacy.) Distance-based methods have the ad-vantage of being computationally very fast.However, this method suffers from a numberof defects (Atkinson & Gray 2005, p. 520; Gray& Atkinson 2003, p. 436). The distance mea-sure loses the information about which wordforms are cognate. Languages change at differ-ent rates (Bergsland & Vogt 1962, Blust 2000,Gray & Atkinson 2003). Individual word mean-ings also change at different rates (Greenberg2005, pp. 108–11; Joos 1964; Kruskal et al.1973; Pagel 2000; Pagel et al. 2007; Pagel &Meade 2006). Finally, borrowing can distortthe distance between languages in ways that re-flect contact, not common ancestry. However,all these problems can be overcome to someextent with newer phylogenetic techniques,briefly described in this and the followingsections.

The loss of information in distance-basedmethods can be addressed by using character-based methods. In character-based methods,particular cognate forms are used to computethe tree. Character-based methods are mostclosely associated with cladistics, which distin-guishes shared innovations from shared reten-tions and uses only the former for constructingthe tree (subgrouping). Two approaches havebeen used for determining the best fit of the treeto the data. In maximum parsimony, the algo-

rithm minimizes the number of character statechanges (in the case of cognate lists, minimizesthe number of replacements of word forms).An alternative approach is the compatibilitycriterion, which minimizes the number ofcharacters that must be assumed to have beeninnovated more than once. Indo-Europeantrees have been constructed using both maxi-mum parsimony (Rexova et al. 2003) and com-patibility (Ringe et al. 2002).

Owing to the complexity of the data, anyphylogeny reconstruction algorithm will pro-duce large numbers of trees, measured accord-ing to the criteria used (e.g., maximum parsi-mony). In fact, the space of possible trees isoften so large that heuristics must be used toidentify the trees to be used in analysis. Thetraditional approach in both distance-based andcharacter-based methods is to base the result ona set of optimal trees. A consensus tree is pro-duced, typically using a majority rules strategy,which posits the nodes in the consensus tree thatare found in at least half the input trees. The ro-bustness of the nodes in the tree relative to thedata is commonly tested with a bootstrappingtechnique (e.g., Holden et al. 2005, p. 60). Inbootstrapping, the original data set is sampledwith replacement (i.e., one is always samplingfrom the full original data set) until a new dataset of the same size is produced. A pseudorepli-cate tree is constructed for the new data set, andthe process is repeated many times. The pseu-doreplicate trees are compared with the origi-nal (consensus) tree, and the robustness of eachnode in the original tree is the percent of thepseudoreplicate trees that contain the node inquestion.

More recently, Bayesian methods have beenapplied to phylogeny reconstruction (Atkinson& Gray 2005, p. 521). In a Bayesian approach,one samples not just the most optimal trees pro-duced, but all possible trees in proportion totheir likelihood (Holden et al. 2005, pp. 60–62).Again, a consensus tree is produced fromthe sample. The proportion of trees with aparticular node in the sample is equivalentto the Bayesian posterior probability of thatnode. A common method used to construct

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the sample to model the posterior probabilitydistribution of trees is a Markov chain MonteCarlo method (see, for example, Gray & Atkin-son 2003, Pagel & Meade 2006). The Bantulanguages have been classified using a distance-based method (Bastin et al. 1999), maximumparsimony (Holden 2002, Rexova et al. 2006),and Bayesian methods (Holden et al. 2005,p. 60; Rexova et al. 2006).

Two other facts about phylogeny recon-struction must be noted here. First, trees pro-duced by the algorithms are unrooted: Theyshow groupings but do not indicate whichgroup is the most distant. Rooting is generallyestablished by using an outgroup, a group thatis agreed to be most distant from all other mem-bers of the data set. Second, the algorithms at-tempt to construct binary trees. The only wayto identify multiple branching is through shortbinary branches and/or failure to construct sta-tistically robust binary branching in part of thetree.

Differentiating Chance Cognationand Borrowing from Cognates

Step 1 in the comparative method, the iden-tification of a set of languages as forming alanguage family, poses a basic problem. Thisselection cannot be done randomly becauseeven with a small number of languages, thenumber of ways in which they can be classi-fied quickly becomes astronomical (see, e.g.,Greenberg 2005, p. 43). Yet most introductionsto comparative linguistics assume that the in-vestigator begins with a set of languages thatare already related.

Nichols (1996) argues that a single diagnos-tic trait, or a small set of traits, is sufficient toidentify a valid linguistic family, but there areserious statistical problems with this approach(see Kessler 2001, p. 32). It is difficult to findany other technique to identify language fami-lies apart from compelling similarities in formand meaning distributed across a set of wordsamong a subset of languages under compari-son. This technique is essentially Greenberg’smethod of multilateral comparison (see the

papers collected in Greenberg 2005). Multilat-eral comparison has often been misunderstoodin the linguistic literature as if Greenberg in-tended it to replace the comparative method.In fact, he intended it only to be an approachto steps 1 and 2 of the comparative method(Greenberg 2001, p. 127). Step 1 is achievedonly jointly with step 2: A set of languagesforms a family because of the presence of similarform-meaning pairings that are concluded to be(putative) cognates.

The crucial problem, then, is to differenti-ate putative cognate forms—those that are pho-netically and semantically similar most likelybecause of common ancestry—from forms inthe data that are similar because of contact(borrowing), sound symbolism, or chance.Greenberg’s primary contention is that thesource of form-meaning similarities in a matrixof word meanings across languages can befairly accurately determined from the distribu-tion pattern of the form-meaning similaritiesin the matrix, as well as from phonologi-cal patterns in the form-meaning similarities(Greenberg 1957, p. 69; see also Greenberg2005, chapter 2). Techniques from biology ex-ploiting these distributional patterns can beapplied to the problems of chance cogna-tion and borrowing. (Sound symbolism is afourth source of similarity, but the likelihood ofsound symbolism is generally minimized by dis-counting or excluding meanings that are likelyto be sound symbolic—i.e., by exploiting acharacteristic distribution pattern across mean-ings.) This approach differs from the standardassumption among users of the comparativemethod, namely that only regular sound cor-respondences can be used to differentiate cog-nates from borrowing and chance resemblance;therefore, until the establishment of soundcorrespondences can be formalized, other ap-proaches remain only tentative. Nevertheless,it appears that a considerable amount of in-formation can be extracted from distributionalpatterns of form-meaning similarities, at leastin the relatively shallow language families towhich these biological phylogeny reconstruc-tion techniques have been applied.


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The likelihood of similarity being due tochance is one that has attracted much atten-tion in historical linguistics, but little can beconcluded from the literature on it. Ringe(1992, 1993) and Greenberg & Ruhlen (1992)have proposed methods to evaluate chance cog-nation, but they are mathematically flawed(Baxter & Manaster Ramer 1996, Greenberg1993, Kessler 2001, Manaster Ramer & Hitch-cock 1996). A more promising approach forevaluating chance cognation is the permuta-tion method, which is not specifically drawnfrom evolutionary biology (Baxter 1995; Baxter& Manaster Ramer 2000; Justeson & Stephens1980; Kessler 2001; Oswalt 1970, 1991). Thepermutation method compares the proportionof form-meaning similarities in the observeddata set to random permutations of the formsacross the meanings to derive a probability thatthe observed form-meaning similarities couldoccur by chance. However, a result indicatingthat form-meaning similarities in the observeddata set are not due to chance gives informa-tion only about the data set as a whole. It doesnot provide information about the validity ofparticular nodes in the tree. Bootstrapping orBayesian posterior probabilities, however, canbe used to address the chance cognation prob-lem because both give a probability of the valid-ity of each node (genetic grouping) in the tree.Of course, some form-meaning similarities maystill be due to chance. The use of character-based methods will provide hypotheses as towhich characters (words) are not contributingto the building of the tree and therefore may bechance similarities.

The problem of differentiating borrowingfrom common ancestry has been addressed intwo general ways. The first is to use tech-niques that assume the data to be treelike andtreat anomalous similarities as derived fromborrowing. Minett & Wang (2003) examine adistance-based method that compares branchlengths of the tree and lexical distances, butthey found that it does not differentiate borrow-ing from cognates. However, a character-basedmethod using maximum parsimony did allowinference of a likelihood of borrowing for char-

acters (words) among the Chinese languages.Nevertheless, Wang & Minett (2005) formalizeHinnebusch’s (1999) proposal that skewing inlexicostatistical percentages may indicate bor-rowing and suggest that this distance-based ap-proach might be useful.

The second is to use techniques that allowreticulation, that is, they allow branches to re-join, representing contact relations and cre-ating phylogenetic networks instead of trees.Bryant et al. (2005) use these techniques torepresent the conflicting signals of languagesthat have undergone significant contact. Thesetechniques allow one to ask how treelike thedata are, rather than assuming the data are tree-like. Bryant et al. show that Indo-European isquite treelike, at least in its basic vocabulary; thesame result is reached by Warnow et al. (2006;see also Holden & Gray 2006, discussed below).Ben Hamed (2005) and Ben Hamed & Wang(2006) show that network techniques appliedto the complex relationships among dialect dif-ferentation, dialect continua, dialect contact,and diglossia in Chinese tend to correlate withknown geographical, linguistic, and populationhistory.

One problem with network techniques isthat most historical linguists believe that thereare few if any instances of true reticulation:One can identify the parent versus the sourceof contact, and even for so-called mixed lan-guages, the contribution of the two is asymmet-ric in systematic ways (Croft 2003). Borrowingcan be differentiated from common ancestryby the distribution of borrowings and theirforms: For instance, some semantic categoriesare less likely to be borrowed, and borrow-ing often links the borrowing language to asingle source language (e.g., Greenberg 1957,p. 71; 2005, p. 38). McMahon et al. (2005) usedifferent weightings of more versus less stablevocabulary to evaluate the form-meaning re-semblances between Quechuan and Aymaran.

Another important route to distinguish-ing cognates from borrowing is to modelthe process of word birth, cognate forma-tion, homoplasy (independent convergence,e.g., by chance), borrowing, and word death and

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compare the results of this model to that of ac-tual language families. Two examples of modelsincluding all these processes are Warnowet al. (2006) and Nicholls & Gray (2006; seeMcMahon & McMahon 2003 for an earliermodel that does not allow for homoplasy). Bothof these models were used to refine a phy-logeny of Indo-European (see below). Bryant(2006) constructs a model comparing radia-tion (and subsequent isolation) versus “networkbreaking” (dialect continua followed by gradualdivergence) and compares it with linguistic dataon Polynesian.

Language Phylogenyand Human Prehistory

The use of techniques from evolutionary biol-ogy in historical linguistics is quite new, andcurrent results must be taken as tentative. Thereview concludes by mentioning some of themore interesting results that have emergedfrom these techniques. The most intensivework has been done on Indo-European, themost intensively studied language family, andBantu and Austronesian, the largest present-daylanguage families, which are nevertheless quiteshallow.

Ringe et al. (2002) use not only lexical cog-nates but also morphological and phonologicaltraits from 24 Indo-European languages (themost ancient members of their branches) and acharacter-based compatability algorithm to de-rive a phylogeny for Indo-European. Their besttree is rooted with Anatolian as the outgroup,on the (not universally accepted) assumptionthat Anatolian is the most distant branch. Theirphylogeny provides evidence on the follow-ing controversial issues in Indo-European phy-logeny: that Tocharian is the most distantbranch after Anatolian, and that Balto-Slavic,Italo-Celtic, and Greco-Armenian are validsubgroups. The position of Albanian is unclear,and Germanic is problematic; Ringe et al. ar-gue that an eastern Indo-European group latercame into contact with western Indo-European.Nakhleh et al. (2005) use a model that includesthe possibility of borrowing (see Warnow

et al. 2006) and argue that Germanic was likelyin contact with Italic, Balto-Slavic, and pos-sibly Greco-Armenian. Rexova et al. (2003)use maximum parsimony on the 200-word listsfor 84 Indo-European languages from Dyenet al. (1992). They conclude that Germanicforms a clade (valid subgroup) with Italic, pos-sibly Celtic, and very possibly Albanian andthat there is an eastern satem group consist-ing of Balto-Slavic and Indo-Iranian. Gray &Atkinson (2003) used Bayesian methods allow-ing for unequal rates of change (inter alia)to construct a phylogeny and attribute a dateand location for proto-Indo-European, specif-ically Anatolia around 9000 years ago (seealso Atkinson & Gray 2006). Their tree treatsTocharian as the most distant branch after Ana-tolian and provides strong evidence for Balto-Slavic and weaker evidence for Germanic-Italic-Celtic. Atkinson et al. (2005) replicatetheir result using the data set from Ringe et al.(2002) (see above) and a stochastic-Dollo modelof vocabulary evolution, which include the pos-sibility of borrowing (see Nicholls & Gray2006). Pagel & Meade (2005) use a Bayesianmethod on a smaller sample of Indo-Europeanlanguages and use the tree to argue that theancestral culture likely had monogamy and adowry system, and shifts away from this systemwere first to polygyny and then to the absenceof a dowry or presence of a bride-price.

Holden et al. (2005) compare a Bayesianphylogeny reconstruction of Bantu withHolden’s (2002) maximum parsimony analysis.Both analyses agree that the northwest Bantugroups are most divergent, with the Bayesiananalysis suggesting they are paraphyletic (i.e.,they do not together form a valid taxon). Theeast, southeast, and southwest languages forma single clade, within which there is a clearEast Bantu group. Holden et al. argue thatthe migration of the Bantu peoples follows thespread of farming into southern Africa. Rexovaet al. (2006) perform maximum parsimony andBayesian analyses of the same lexical data incombination with phonological and grammati-cal characters. They also find a single clade forthe east, southeast, and southwest groups and


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conclude that there was a single migration fromthe equatorial rainforests to the areas southand east. Holden & Gray (2006) use networkmodels to ascertain why the Bantu group isnot treelike in certain respects. They concludethat West Bantu languages radiated rapidly butwithout much contact, whereas East Bantu andeast Central Bantu languages appear to have hadmuch contact leading to borrowing. Holden &Mace (2003, 2005) use the maximum parsimonytree to argue that matrilineal descent was lostas cattle were adopted in prehistoric southernAfrica.

Gray & Jordan (2000) use a parsimony anal-ysis on 77 Austronesian languages with 5185lexical items from Blust’s unpublished Austrone-sian Comparative Dictionary to argue that thestructure of the language family is stronglytreelike, with greatest diversity in Taiwan, andthat this analysis supports the express trainhypothesis of relatively rapid colonization ofOceania by the ancestral Austronesians. How-ever, Greenhill & Gray (2005) show thatapplying bootstrapping to the original studydemonstrates it is not that robust. They useBayesian methods to construct a tree that fitsmore closely with the traditional historical lin-guistic analysis, which still places the origin inTaiwan but does not necessarily entail a rapidexpansion across Oceania. A network analysisindicates that the major groups in Austronesianare treelike but that the deeper branchings areless treelike because of the lack of signal in thedata set.

Dunn et al. (2005) use a maximum par-simony analysis of typological traits, ratherthan lexical traits, to construct phylogeniesof Oceanic and Papuan languages of IslandMelanesia. They compare their analysis to thephylogeny of the Oceanic languages in that areaand find a high degree of corroboration. The

Papuan languages in the area do not displaymuch lexical resemblance, but Dunn et al. ar-gue that the use of typological traits reveals aphylogeny that is apparently lost owing to lexi-cal replacement. Typological traits are avoidedin comparative linguistics because they havefew possible values (and are thus highly proneto chance resemblance), they diffuse throughcontact relatively easily, their values are of-ten not independent (e.g., they are linked byimplicational universals), and their values areoften externally (functionally) motivated (an-other source of convergence). Some of theseissues are raised in a critique by Donohue &Wichmann (2007); see also the response byDunn et al. (2007). Although the result fromDunn et al. (2005) is surprising to a histor-ical linguist, it may be that a cluster of ty-pological traits will provide more precision inclassification than will individual traits; alsosome typological traits are quite stable andtherefore may be useful indicators of phy-logeny. However, Gray (2005) notes someweaknesses in the analysis from Dunn et al.,and the use of typological traits in phylogenyreconstruction remains to be investigatedfurther.

As with the employment of qualitative con-cepts from evolutionary biology in theories oflanguage change, the application of quanti-tative methods from evolutionary biology tophylogeny reconstruction in comparative lin-guistics is in its infancy. The application toaccepted language families using establishedcognates provides a new perspective on out-standing problems in those families and allowsfor a link to human prehistory. However, fur-ther progress in adapting methods to linguisticphenomena is required before they can be usedconfidently to investigate controversial or as yetundiscovered language families.

DISCLOSURE STATEMENT

The author is not aware of any biases that might be perceived as affecting the objectivity of thisreview.

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AR355-FM ARI 14 August 2008 14:6

Annual Review ofAnthropology

Volume 37, 2008Contents

Prefatory Chapter

The Human Brain Evolving: A Personal RetrospectiveRalph L. Holloway � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 1

Archaeology

Evolution in ArchaeologyStephen Shennan � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �75

The Archaeology of ChildhoodJane Eva Baxter � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 159

The Archaeological Evidence for Social EvolutionJoyce Marcus � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 251

Sexuality Studies in ArchaeologyBarbara L. Voss � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 317

Biological Anthropology

The Effects of Kin on Primate Life HistoriesKaren B. Strier � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �21

Evolutionary Models of Women’s Reproductive FunctioningVirginia J. Vitzthum � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �53

Detecting the Genetic Signature of Natural Selection in HumanPopulations: Models, Methods, and DataAngela M. Hancock and Anna Di Rienzo � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 197

Linguistics and Communicative Practices

Linguistic Anthropology of EducationStanton Wortham � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �37

A Historical Appraisal of Clicks: A Linguistic and Genetic PopulationPerspectiveTom Guldemann and Mark Stoneking � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �93

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Linguistic Diversity in the CaucasusBernard Comrie � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 131

Evolutionary LinguisticsWilliam Croft � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 219

Reproduction and Preservation of Linguistic Knowledge: Linguistics’Response to Language EndangermentNikolaus P. Himmelmann � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 337

Sociocultural Anthropology

Evolutionary Perspectives on ReligionPascal Boyer and Brian Bergstrom � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 111

Reproduction and Inheritance: Goody RevisitedChris Hann � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 145

Assisted Reproductive Technologies and Culture ChangeMarcia C. Inhorn and Daphna Birenbaum-Carmeli � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 177

Post-Post-Transition Theories: Walking on Multiple PathsManduhai Buyandelgeriyn � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 235

From Resilience to Resistance: Political Ecological Lessons fromAntibiotic and Pesticide ResistanceKathryn M. Orzech and Mark Nichter � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 267

Violence, Gender, and SubjectivityVeena Das � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 283

Demographic Transitions and ModernityJennifer Johnson-Hanks � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 301

The Anthropology of Crime and CriminalizationJane Schneider and Peter Schneider � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 351

Alternative Kinship, Marriage, and ReproductionNancy E. Levine � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 375

Theme 1: Evolution in Anthropology

Evolutionary Models of Women’s Reproductive FunctioningVirginia J. Vitzthum � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �53

Evolution in ArchaeologyStephen Shennan � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �75

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A Historical Appraisal of Clicks: A Linguistic and Genetic PopulationPerspectiveTom Guldemann and Mark Stoneking � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �93

Evolutionary Perspectives on ReligionPascal Boyer and Brian Bergstrom � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 111

Detecting the Genetic Signature of Natural Selection in HumanPopulations: Models, Methods, and DataAngela M. Hancock and Anna Di Rienzo � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 197

Evolutionary LinguisticsWilliam Croft � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 219

Post-Post-Transition Theories: Walking on Multiple PathsManduhai Buyandelgeriyn � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 235

The Archaeological Evidence for Social EvolutionJoyce Marcus � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 251

From Resilience to Resistance: Political Ecological Lessons fromAntibiotic and Pesticide ResistanceKathryn M. Orzech and Mark Nichter � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 267

Theme 2: Reproduction

The Effects of Kin on Primate Life HistoriesKaren B. Strier � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �21

Reproduction and Inheritance: Goody RevisitedChris Hann � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 145

The Archaeology of ChildhoodJane Eva Baxter � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 159

Assisted Reproductive Technologies and Culture ChangeMarcia C. Inhorn and Daphna Birenbaum-Carmeli � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 177

Demographic Transitions and ModernityJennifer Johnson-Hanks � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 301

Sexuality Studies in ArchaeologyBarbara L. Voss � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 317

Reproduction and Preservation of Linguistic Knowledge: Linguistics’Response to Language EndangermentNikolaus P. Himmelmann � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 337

Alternative Kinship, Marriage, and ReproductionNancy E. Levine � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 375

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