We test for universal patterns in cultural evolution by Guttman scaling on two different worldwide samples of archaeological traditions and on well-known archaeological sequences. The evidence is generally consistent with universal evolutionary sequences. We also present evidence for some punctuated evolutionary events.

Scalograms for eight regional evolutionary sequences, based on our revision of Murdock and Provost 1973. Numbers in the bottom rows refer to case numbers in the Outline of Archaeological Traditions. Question marks denote uncertain codings and potential scale errors.
Dendrogram of the 15-item Guttman scale variables, produced using SPSS 10.0 Hierarchical Cluster routine, the centroid method, and squared Euclidean distance measure. Labels A, B, C, and D denote clusters of variables that match groups of traits that the scalograms suggest co-evolve.

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PETER N. PEREGRINE

CAROL R. EMBER

MELVIN EMBER

Universal Patterns in Cultural Evolution: An

Empirical Analysis Using Guttman Scaling

ABSTRACT We test for universal patterns in cultural evolution by Guttman scaling on two different worldwide samples of archae-

ological traditions and on well-known archaeological sequences. The evidence is generally consistent with universal evolutionary se-

quences. We also present evidence for some punctuated evolutionary events. [Keywords: cultural evolution, cross-cultural research,

scaling, anthropological theory]

WHILE IT IS WIDELY ACCEPTED THAT CULTURES

have generally become more complex over time,

it is not widely accepted that societies generally develop

traits in ordered evolutionary sequences. Building on the

comparative ethnographic work of Linton Freeman (1957)

and Robert Carneiro (1962), we test here for universal evo-

lutionary sequences, primarily using Guttman scales on data

from two worldwide samples of archaeological traditions.

GUTTMAN SCALING

Carniero (1962) suggested that Guttman scaling held great

potential for the study of cultural evolution, as it was de-

veloped to identify unidimensional processes. This is ac-

complished in Guttman scaling by identifying a clear hier-

archy among a group of scale items. At the top of the scale

are traits that, when present, tell one that other traits be-

low should also be present (Guttman 1950). There are ob-

vious evolutionary implications if one finds that traits

form a Guttman scale—"the order in which the traits are

arranged, from bottom to top, is the order in which the so-

cieties have evolved them" (Carneiro 1970:837).

We agree that Guttman scaling is particularly useful

for identifying patterns of cultural evolution because the

hierarchy inherent in a Guttman scale suggests an evolu-

tionary order. To date, however, only a handful of such scales

have been proposed (e.g., Bowden 1969; Carniero 1962,

1970; Carneiro and Tobias 1963; McNett 1970; Naroll

1956), and only one general Guttman scale of cultural

evolution has been put forward—Freeman's "Folk–Urban

Continuum" Scale (Freeman 1957; see also Freeman and

Winch 1957). The Freeman scale, which emerged from his

examination of 52 ethnographically described cultures,

suggests that 11 traits develop as cultures evolve from "folk"

to "urban" (see the order shown in Table 1, column A).

Freeman was limited in the sample of ethnographic

cases he was able to use and was only able to examine

cases from the "ethnographic present." Because this scale

is one that is intended to model an evolutionary process,

testing it in a single time period may not be satisfactory.

After all, such a scale may fit the "ethnographic present"

but may not fit a sample derived from the entire range of

human history. For this reason we attempted to replicate

Freeman's scale using a random sample of 20 cases, vary-

ing both temporally and geographically, that we selected

from the electronic Human Relations Area Files (eHRAF)

Collection of Archaeology.

The eHRAF Collection of Archaeology provides indexed

and searchable primary documents on cases selected by

random sampling and geographical time series from the

Outline of Archaeological Traditions (Peregrine 2001a). The

Outline of Archaeological Traditions is a catalogue of all

known archaeological traditions covering the entire globe

and the entire prehistory of humankind and, thus, is a

comprehensive sampling universe of prehistoric societies.

While relatively small, our 20-case sample—chosen as it

was from a comprehensive sampling universe by random

sampling—should reflect the entire range of variation

among prehistoric human societies and, thus, should miti-

gate any bias found among societies in the "ethnographic

present." If Freeman's Guttman scale applies to all human

societies at all times in human history, then we should be

able to reproduce it using only these 20 cases.

AMERICAN ANTHROPOLOGIST 106(1):145–149. C OPYRIGHT © 2004, A MERICAN ANTHROPOLOGICAL ASSOCIATION

A basic problem we encountered in applying Free-

man's scale to prehistoric cases was that some of the traits

are not easily measurable from the archaeological record.1

Two that proved especially difficult were the presence of

secondary tools and the presence of full-time religious spe-

cialists. In both cases, the level of inference would be quite

high, and we decided that rather than incorporate them

and introduce error, we should drop those items. In addi-

tion, none of the sample cases had money, so we were un-

able to use that variable in our scale. Scaling the remain-

ing eight items replicated Freeman's results (as shown in

Table 1, column B) and resulted in a near-perfect scale with

TABLE 1. Three Guttman scales of cultural evolution. Lower numbered items presumably evolve before higher-numbered items. Column A

is the scale developed by Freeman (1957), column B is our version of the Freeman scale, shortened to apply to archaeological cases, column

C is the scale we developed from Murdock and Provost 1973 and is also applicable to archaeological cases.

A: Freeman Scale B: Revised Freeman Scale C: 15-Item Murdock-Provost Scale

1. Trade with other societies 1. Intersocietal trade 1. Ceramic production

2. Subsistence economy based primarily

2. on agriculture or pastoralism

2. Subsistence economy based on food

2. production

2. Presence of domesticates

3. Social stratification or slavery 3. Social stratification or slavery 3. Sedentarism

4. Full-time governmental specialists 4. Full-time government specialists 4. Inegalitarian (status or wealth

4. differences)

5. Full-time religious or magical

5. specialists

5. Full-time craft specialists 5. Density > 1 person/mi2

6. Secondary tools 6. Political state of 10,000 in population 6. Reliance on food production

7. Full-time craft specialists 7. Towns exceeding 1,000 in population 7. Villages > 100 persons

8. A standard medium of exchange 8. Writing 8. Metal production

9. A state of at least 10,000 in population 9. Social classes present

10. Towns exceeding 1,000 in

10. population

10. Towns > 400 persons

11. Complex, unambiguous, written

11. language

11. State (3+ levels of hierarchy)

12. Density > 25 persons/mi2

13. Wheeled transport

14. Writing of any kind

15. Money of any kind

FIGURE 1. Scalograms for eight regional evolutionary sequences, based on our revision of Freeman's (1957) 11-item scale. Numbers in the

bottom rows refer to case numbers in the Outline of Archaeological Traditions. Question marks denote uncertain codings and potential scale

errors.

146 American Anthropologist • Vol. 106, No. 1 • March 2004

only two scale errors (CR = .988; CS = .943; MMR = .781).2

From this replication we conclude that there are gen-

eral sequences in cultural evolution that hold for both his-

toric and prehistoric cases. While not all cases must evolve

in precisely this way, a valid Guttman scale cannot occur

unless most cases behave in the manner described in the

scale. We have some concern, however, with the fact that

other scholars have noted that Guttman scales with fewer

than nine or ten items may produce a high coefficient of

reproducibility (over .9) by chance (Schooler 1968). Our

scale, composed of only eight items, should be approached

with caution but fits the data with such accuracy that

chance seems an unlikely cause. Indeed, it far exceeds

standard guidelines for evaluating the acceptability of a

Guttman scale (CR > .9; MMR < .9; CS > .6; see McIver and

Carmines 1981:70).

But even if this apparent order to the evolution of cul-

tural traits is not a statistical artifact, did these traits actu-

ally evolve in the stipulated sequence in many, if not

most, parts of the world? To answer this question we ex-

amined individual sequences of cultural evolution in eight

world regions: Yellow River Valley, Nile River Valley, West

Africa, Mesopotamia, Indus River Valley, Highland Peru,

Lowland Peru, and Highland Mesoamerica. The sequences

were derived from the Outline of Archaeological Traditions

(Peregrine 2001a), and scalograms for each sequence are

shown in Figure 1.3 Question marks illustrate places where

either scale errors appear or in which there were missing

data (which we took to be scale errors—if the scale is accu-

rate, then traits should be readily apparent). In all eight re-

gions cultural traits appear primarily in the order sug-

gested by Freeman's Guttman scale.

EXPANDED GUTTMAN SCALE OF CULTURAL EVOLUTION

Because the Freeman scale had only eight items and, thus,

may have produced a high coefficient of reproducibility

by chance, we decided to develop a scale with additional

FIGURE 2. Scalograms for eight regional evolutionary sequences, based on our revision of Murdock and Provost 1973. Numbers in the

bottom rows refer to case numbers in the Outline of Archaeological Traditions. Question marks denote uncertain codings and potential scale

errors.

Peregrine, Ember, and Ember • Universal Patterns in Cultural Evolution 147

items based on data coded by the first author (Peregrine

2001b, 2003). The data were derived from entries in the

Encyclopedia of Prehistory (Peregrine and Ember 2001–02)

and based on a ten-item scale of cultural complexity de-

veloped by Murdock and Provost (1973; also see Chick

1997). The data were recoded into 15 present–absent vari-

ables and then scaled. We found they formed a Guttman

scale (CR = .968; CS = .892; MMR = .709) with the order

presented in Table 1, column C. This 15-item Guttman

scale is large enough that scaling is improbable by chance,

and because it is based on 289 cases, it also avoids the po-

tential problem of the small sample size involved in our

replication of the Freeman scale. Thus, this larger Guttman

scale reinforces the conclusion that there are universal

patterns in cultural evolution.

Figure 2 presents scalograms based on this scale for eight

regional evolutionary sequences. While the sequences sup-

port the Guttman scale, there is a consistent error that can

be seen in five of the eight sequences—ceramic produc-

tion is not present before domesticates. This error occurs

only eight times in the entire 289-case data set, and six are

represented in these eight sequences. All occur in loca-

tions where domesticates are thought to have been inde-

pendently developed, which may hint at an explanation

for this repeated error. But why ceramics, as a storage or

cooking technology, should go hand-in-hand with the de-

velopment of domesticates is a question that requires fur-

ther research.

PUNCTUATED EVENTS IN CULTURAL EVOLUTION

Evidence for punctuated evolutionary events, where sev-

eral traits appear together, is clear in both Figures 1 and 2.

In Figure 1 it appears that, while trade may evolve alone or

with agriculture, once social stratification evolves both

government and craft specialists also evolve. Similarly,

once the population of polities grows above 10,000, both

cities and writing tend to appear. Such evolutionary leaps

are clearer in Figure 2, where it appears that once sedenta-

rism evolves so does social inequality and a reliance on do-

mesticates. A second leap appears to occur when metals

evolve, as social classes, towns, and political states appear

to evolve as well. The presence of these punctuated events

may help to explain why, despite the general rejection of

the idea that there are universal patterns in cultural evolu-

tion, anthropologists still tend to classify cultures typo-

logically, for example, as bands, tribes, chiefdoms, or states

(Service 1962). Commonly used typologies may reflect the

regular co-evolution of some cultural traits.

Cluster analysis provides a means to test whether

some traits tend to co-evolve, and Figure 3 presents the re-

sults of a cluster analysis of the 15-point Guttman scale.

There appear to be two major groups that match the order

of the 15-point Guttman scale and divide at the Metals

variable. The variables below Metals on the scale form one

cluster (A), while those above form a second cluster (B).

Within the higher cluster, the variables State, Towns >

400, Classes, and Metals form a unique cluster (C), while

FIGURE 3. Dendrogram of the 15-item Guttman scale variables, produced using SPSS 10.0 Hierarchical Cluster routine, the centroid method,

and squared Euclidean distance measure. Labels A, B, C, and D denote clusters of variables that match groups of traits that the scalograms

suggest co-evolve.

148 American Anthropologist • Vol. 106, No. 1 • March 2004

Money, Writing, Wheel, and Density > 25 form another

cluster (D). These clusters appear identical to the punctuated

evolutionary changes evident in the scalograms and sug-

gest that both reflect the co-evolution of specific groups of

cultural traits. One might see these as evolutionary "stages,"

similar to those proposed by a number of anthropologists

in the middle of the last century that are now considered

highly suspect (Blanton et al. 1996).

We conclude that there are universal patterns in cul-

tural evolution. Cultural traits evolve in regular ways, and

some traits appear to co-evolve in punctuated evolutionary

events that may parallel the typologies through which an-

thropologists frequently classify the cultures of the world.

PETER N. PEREGRINE Department of Anthropology, Lawrence

University, Appleton, WI 54911

CAROL R. EMBER Human Relations Area Files at Yale University,

New Haven, CT 86511

MELVIN EMBER Human Relations Area Files at Yale University,

New Haven, CT 86511

NOTES

1. All cases were coded in random order by the first author.

2. Guttman scale statistics were calculated using Anthropac 3.2

and the minimized errors method. CR refers to the coefficient of

reproducibility, which measures the degree of scalability of the em-

pirical data. CS refers to the coefficient of scalability, which is a

measure of a scale's ability to predict item responses in comparison

to predictions based on marginal frequencies and is, thus, basically

a proportional reduction in error (PRE) statistic. Finally, MMR re-

fers to the minimal marginal reproducibility, which, as its name

implies, is a measure of reproducibility based on the marginal fre-

quencies for each item.

3. Data for these scalograms were derived from entries in the Ency-

clopedia of Prehistory (Peregrine and Ember 2001–02) by the first

author and were coded in random order (see Peregrine 2003).

While not nearly as detailed as the information in the eHRAF Col-

lection of Archaeology, the entries in the Encyclopedia of Prehistory

provided enough information to make confident codings in most

cases. In those where codings were unclear, additional sources, in-

cluding the eHRAF Collection of Archaeology, were examined.

REFERENCES CITED

Blanton, Richard, Gary Feinman, Stephen Kowalewski, and Peter

N. Peregrine

1996 A Dual-Processual Theory for the Evolution of Mesoameri-

can Civilization.Current Anthropology 37:1–14.

Bowden, Edgar

1969 An Indexof Sociocultural Development Applicable to Pre-

civilized Societies. American Anthropologist 71:454–461.

Carniero, Robert L.

1962 ScaleAnalysis asan Instrumentfor the Study of CulturalEvo-

lution. Southwestern Journal of Anthropology 18:149–169.

1970 ScaleAnalysis, EvolutionarySequences, and the Rating of

Cultures. In A Handbook of Method in Cultural Anthropology.

Raoul Naroll and Ronald Cohen, eds. Pp. 834–871. Garden City,

NY: Natural History Press.

Carneiro, Robert L., and Stephen F. Tobias

1963 The Application of Scale Analysis tothe Study of Cultural

Evolution. Transactions of the New York Academy of Sciences,

ser. 2, 26:196–207.

Chick, Gary

1997 Cultural Complexity: The Concept and Its Measurement.

Cross-Cultural Research 31(4):275–307.

Freeman, Linton C.

1957 An Empirical Test of Folk-Urbanism. Ann Arbor: Uni versity

Microfilms, No. 23.

Freeman, Linton C., and Robert F. Winch

1957 Societal Complexity: An EmpiricalTest of a Typology of So-

cieties. American Journal of Sociology 62:461–466.

Guttman, Louis L.

1950 The Basisfor Scalogram Analysis. In Measurement and Pre-

diction. Samuel A. Stouffer, ed. Pp. 60–90. Princeton: Princeton

University Press.

McIver, John P., and Edward G. Carmines

1981 Unidimensional Scaling. Beverly Hills, CA: Sage .

McNett, Charles W., Jr.

1970 A Settlement Pattern Scaleof Cultural Complexity. In A

Handbook of Method in Cultural Anthropology. Raoul Naroll

and Ronald Cohen, eds.Pp. 872–886.Garden City, NY: Natural

History Press.

Murdock, George P., and Catarina Provost

1973 Measurem ent of Cultural Complexity. Ethnology 12:379–392.

Naroll, Raoul

1956 A Prelimi nary Index of Social Development. American An-

thropologist 59:664–68 7.

Peregrine, Peter N.

2001a Outline of ArchaeologicalTraditions. New Haven, CT: Hu-

man Relations Area Files.

2001b Cross-Cultural Comparative Approaches in Archaeology.

Annual Review of Anthropology 30:1–18.

2003 Atlas of Cultural Evolution. World Cultures 14(1):2–88.

Peregrine, Peter N., and Melvin Ember

2001–2002 Encyclopedia of Prehistory, 9 vols.New York: Kluwer

Academic/Plenum Publishers.

Schooler, Carmi

1968 A Note of Extreme Cautionon the Use of Guttman Scales.

American Journal of Sociology 74:296–301.

Service, Elman

1962 Primitive Social Organization. Ne w York: Random House.

Peregrine, Ember, and Ember • Universal Patterns in Cultural Evolution 149

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... One example that has been investigated in previous work is the emergence of bureaucratic forms of governance, which tend to develop around the time when polities first extend political control beyond more than a day's round trip from the capital (20). A related idea is that, if there are strong relationships between these variables and if change is relatively rapid, then societies may tend to evolve toward certain types of sociopolitical organization based on associations between certain combinations of traits (3,24,57). Cluster analysis of PC1 shows some initial support for this idea, indicating a clear distinction between large societies that exhibit many of the nonscale features of complexity and smaller societies that lack most of these features, with other potential groupings within these clusters (SI Appendix, SI Discussion and Figs. S12 and S13). ...

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Social inequality is now pervasive in human societies, despite the fact that humans lived in relatively egalitarian, small-scale societies across most of our history. Prior literature highlights the importance of environmental conditions, economic defensibility, and wealth transmission for shaping early Holocene origins of social inequality. However, it remains untested whether the mechanisms that drive the evolution of inequality in recent human societies follow a similar trajectory. We conduct the first global analysis of pathways to inequality within modern human societies using structural equation modeling. Our analytical approach demonstrates that environmental conditions, resource intensification, and wealth transmission mechanisms impact various forms of social inequality via a complex web of causality. We further find that subsistence practices have a direct impact on some institutionalized forms of inequality. This work identifies drivers of social inequality in the modern world and demonstrates the application of structural equation modeling methods to investigate complex relationships between elements of human culture.

  • Garry Chick Garry Chick

Cultural complexity is one of the most commonly used variables in cross-cultural research. It has often been used as a measure of cultural evolution and has been shown to correlate with numerous other variables. At least eight measures of cultural complexity have been constructed since the late 1940s. The purpose of this article is to examine three of them, those proposed by Carneiro, Murdoch and Provost, and Naroll. Particular attention will be devoted to the validity of these measures. Factor analysis and reliability analysis indicate that Murdoch and Provost's index, designed for use with the Standard Cross-Cultural Sample, although reliable, has two dimensions rather than one and may lack content and construct validity. A case is made for the use of the logarithm of the size of the largest settlement in a society as a measure of cultural complexity, as suggested by Naroll.

  • Peter N. Peregrine Peter N. Peregrine

The Atlas of Cultural Evolution provides basic data on the evolution of cultural complexity using the Outline of Archaeological Traditions sample. The Outline of Archaeological Traditions constitutes a sampling universe from which cases can be drawn for diachronic cross-cultural research, an activity I refer to as archaeoethnology. Data for the Atlas were drawn from entries in the Encyclopedia of Prehistory, a nine volume work providing summary information on all cases in the Outline of Archaeological Traditions, thus the Atlas also demonstrates the utility of the Encyclopedia of Prehistory as a basic tool for archaeoethnology. I suggest that a more sophisticated tool for archaeoethnology, the eHRAF Collection of Archaeology, be used to further test and refine the cultural evolutionary trends put forward here.

  • Peter N. Peregrine Peter N. Peregrine

Cross-cultural comparative approaches have been used widely in archaeological research, yet to date none seem to have achieved their full potential. Synchronic cross-cultural comparisons have provided a number of material correlates of behavior, as well as a few causal and noncausal associations that allow behavior to be inferred from material remains. However, large areas of material culture, such as ceramics and lithics, have not yet been subject to extensive comparative analysis, and thus large areas of archaeological research that might be aided by synchronic comparative findings have been left unassisted. Diachronic cross-cultural comparisons have been used extensively to chart and analyze cultural evolution. However, these comparisons are typically based on grab-bag samples and only rarely employ statistics to aid in the discovery or testing of evolutionary patterns. New research tools providing a statistically valid sampling universe and information resources for coding archaeological data are being developed to facilitate cross-cultural comparisons.

  • Linton C. Freeman Linton C. Freeman
  • Robert F. Winch

The abstract for this document is available on CSA Illumina.To view the Abstract, click the Abstract button above the document title.

  • Carmi Schooler Carmi Schooler

Since the change occurence of the various scale types is a function of the joint probability of the occurrence of their constituent responses, it is possible that Scalograms meeting currently acceptable levels of Scalabity and Reproducibility can occur by chance alone. Even Chilton's method, which determines whether the observed Reproducibility is significantly better than chance, does not guarantee that a scale is homogeneous; significant Reproductibility can occur even when three of six items are unrelated. Although very strict adherence to all of Ford's criteria might eliminate most chance-derived scales, the rule-of-thumb origins of these criteria limit their usefulness as rational proof that Guttman Scales are homogeneous.