Table Of ContentQuantitative Archaeology and Archaeological Modelling
Catalin Nicolae Popa
Modelling
Identities
A Case Study from the Iron Age of
South-East Europe
Quantitative Archaeology and Archaeological
Modelling
Series Editors
Andrew Bevan, University College London, London, United Kingdom
Oliver Nakoinz, University of Kiel, Kiel, Germany
More information about this series at http://www.springer.com/series/14342
Catalin Nicolae Popa
Modelling Identities
A Case Study from the Iron Age
of South-E ast Europe
Catalin Nicolae Popa
Leiden University, Leiden, Netherlands
ISSN 2366-5998 ISSN 2366-6005 (electronic)
Quantitative Archaeology and Archaeological Modelling
ISBN 978-3-319-63265-0 ISBN 978-3-319-63267-4 (eBook)
https://doi.org/10.1007/978-3-319-63267-4
Library of Congress Control Number: 2017948646
© Springer International Publishing AG, part of Springer Nature 2018
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of
the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation,
broadcasting, reproduction on microfilms or in any other physical way, and transmission or information
storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology
now known or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication
does not imply, even in the absence of a specific statement, that such names are exempt from the relevant
protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in this book
are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the
editors give a warranty, express or implied, with respect to the material contained herein or for any errors
or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims
in published maps and institutional affiliations.
Printed on acid-free paper
This Springer imprint is published by the registered company Springer Science+Business Media, LLC
part of Springer Nature.
The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
Can we talk of large ethnic groups in South-East Europe during the Late Iron Age?
Since ancient authors, such as Strabo, provide us with the names of numerous peo-
ples, archaeologists have made great efforts to link them with particular material
culture forms. But are these identity divisions indeed supported by archaeological
finds? Did prehistoric people feel that they were part of these large ethnic entities?
In this book I address such questions by investigating the funerary practices of Late
Iron Age people with the aid of statistical modelling.
This volume comes out of my Ph.D. research, conducted between 2009 and 2014
at the University of Cambridge. I became highly interested in the Late Iron Age of
South-East Europe throughout my school years because this period is often regarded
as inhabited by the ancestors of many modern European nations: Gauls, Celt-
Iberians, Thracians, Illyrians etc. This point is particularly valid for my native coun-
try, Romania, a nation that traces its roots back to the Late Iron Age people called
Dacians or Geto-Dacians. However, as I delved into the identity literature through-
out my university years, I started to question many of the ideas that I had read about
“my” Dacian forefathers. What did it mean to be a Dacian? What made someone a
Dacian rather than something else? And why were they “my” or anyone else’s fore-
fathers in the first place? I was surprised to discover that such question had not been
asked before. It became clearer and clearer that much of what we know about the
Dacians was born out of the ambition of some Romanian scholars to populate the
Late Iron Age past with their nations’ ancestors. Yet, if that is indeed the case, can
one speak of Dacians, Getae or any other identity group when doing a critical analy-
sis of the archaeological record? With these questions in mind, I embarked on the
long and winding road of Ph.D. research.
It may appear unusual that statistical modelling, of all things, was the method
of choice for answering questions of group identity. Is it though? There is no doubt
that, when looked at in detail, group identity involves a lot of personal, profoundly
subjective choices. These choices can be led by the desire for personal gain, by a
sense of pre-existing natural order, by previous personal experiences and many
other factors. It thus seems logical that gaining a comprehensive understanding
of such a complex process requires a highly meticulous, qualitative analysis.
v
vi Preface
However, with the risk of being reductionist, in my research I was only interested
in finding broad manifestations of group identity. When put in very simple terms,
much of our current knowledge of group identity points to it being the result of
people’s identification with or differentiation from the practices carried out by
other individuals: identity comes out of some type of practice comparisons. And
comparing is one thing that statistics excels at.
Therefore, statistical modelling occupies a central role in this book. Extensive
parts are dedicated to illustrating the modelling technique, which is employed to
compare archaeological information. The method consists of a highly flexible simi-
larity algorithm combined with clustering procedures. Through its flexibility, the
algorithm can be adapted to incorporate and emphasise a large spectrum of elements
that researchers may consider to be important. This feature also facilitates the trans-
fer of the method to other contexts with relative ease.
The book also aims to show the compatibility of archaeological theory and sta-
tistical modelling. The discussions from archaeological theory rarely find method-
ological implementations through statistical methods, since the former is seen as
relating to qualitative issues, while the latter is perceived as being exclusively quan-
titative in nature. In this volume theoretical issues form an integrative part of data
preparation, method development and results interpretation. The steps of the analy-
sis are grounded in theoretical concepts, which are discussed in varying degrees of
detail.
Finally, the volume takes the form of a narrative rather than a manual. The inten-
tion is not to teach the workings of particular statistical methods, but rather to answer
a complex archaeological question with the aid of statistical modelling. The reader
is walked through each stage of the investigation procedure, from data preparation
and method adaptation to evaluating and interpreting the results in their broader
context. While some parts may be more difficult to comprehend, much of the analy-
sis procedure and general argument should be relatively easy to follow with a mini-
mum of prior knowledge. To facilitate text understanding, when describing data and
statistical results, italics were used for the names of variables (e.g. object category
1) and underlining was employed for the value of variables (e.g. weapon).
I hope that the book will prove useful to both statistics users and readers with an
interest in the Late Iron Age of Europe or issues of prehistoric identity.
Leiden, Netherlands Catalin Nicolae Popa
August 2016
Acknowledgements
This volume would not have been possible without the funding provided by the Arts
and Humanities Research Council UK, the Cambridge European Trusts and the
Raţiu Family Foundation, which allowed me to complete my Ph.D. research. I am
also grateful for the support of my host institutions, the University of Cambridge,
the Excellence Cluster Topoi, Freie Universität Berlin and Leiden University.
I would like to express my thanks to the numerous people who have guided me
or provided feedback throughout the writing of this volume: Simon Stoddart, Gelu
Florea, Aurel Rustoiu, Mariana Egri, Oliver Nakoinz, Kerstin Hofmann, Martin
Millet, Stephen Shennan, Kris Lockyear, John Robb and Sheila Kohring.
My deepest gratitude goes to those who have been close to me throughout the
years and have endured bravely my incessant ranting about archaeology and statis-
tics: Barbara Hausmair, Maikel Kuijpers, Tiago Hermenegildo, Bela Dimova,
Radmila Balaban and Marija Ljustina.
vii
Contents
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 General Introduction of Research Area and Topic . . . . . . . . . . . . . . 1
1.2 State of Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Justification of Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.4 Structure of Volume . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2 Final Resting Place: The Archaeological Data . . . . . . . . . . . . . . . . . . . 15
2.1 Death and Burial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.1.1 Theoretical Concepts About Death:
The Potential of Burials in Archaeology . . . . . . . . . . . . . . . 15
2.1.2 Practical Arguments for Using Burials . . . . . . . . . . . . . . . . 19
2.2 Data Limits and Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.2.1 Spatial Limits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.2.2 Chronological Limits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.2.3 Void of Burials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.2.4 Burials in the Void . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.3 Data Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.3.1 Data Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.3.2 Data Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.3.3 Tables Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.3.4 Queries and Reports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.4 Object Categorization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.4.1 Theoretical Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.4.2 Construction of Categories . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.4.3 V ariables Description: General Information . . . . . . . . . . . . 35
2.4.4 V ariables Description: Functional Categories . . . . . . . . . . . 36
2.4.5 Variables Description: Typological Categories . . . . . . . . . . 37
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
ix
x Contents
3 The Working Apparatus: Identity and Statistics . . . . . . . . . . . . . . . . . 51
3.1 The Theoretical Tools: Identity Theory . . . . . . . . . . . . . . . . . . . . . . 52
3.1.1 Identity Theory Concepts in Archaeology . . . . . . . . . . . . . . 52
3.1.2 I dentity: Directly Implementable Ideas . . . . . . . . . . . . . . . . 55
3.2 The Practical Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.2.1 Statistical Analysis: Theoretical Considerations . . . . . . . . . 57
3.2.2 Statistical Analysis: The Use of R . . . . . . . . . . . . . . . . . . . . 58
3.2.3 Statistical Analysis: The Use of SPSS . . . . . . . . . . . . . . . . . 71
3.2.4 Spatial Analysis: The Use of ArcGIS . . . . . . . . . . . . . . . . . 72
3.3 The Road to the Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
3.3.1 Weight Calibration Example . . . . . . . . . . . . . . . . . . . . . . . . 76
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
4 A Complex Answer. Results Description . . . . . . . . . . . . . . . . . . . . . . . . 87
4.1 General Description and Validation . . . . . . . . . . . . . . . . . . . . . . . . . 87
4.2 Group 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
4.3 Group 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
4.4 Group 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
4.5 Group 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
4.6 Group 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
4.7 Group 6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
4.8 Group 7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
4.9 Partially Clustered Graves . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
4.10 Non-clustered Graves . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
5 F rom Large to Small. Results Discussion . . . . . . . . . . . . . . . . . . . . . . . 123
5.1 D iscussion of the Statistically Derived Groups . . . . . . . . . . . . . . . . 123
5.1.1 General Groups Overview . . . . . . . . . . . . . . . . . . . . . . . . . . 123
5.1.2 Group 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
5.1.3 Group 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
5.1.4 Group 4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
5.1.5 Group 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
5.1.6 Group 6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
5.1.7 Group 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
5.1.8 Group 7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
5.1.9 T he Clusters and Group Identity . . . . . . . . . . . . . . . . . . . . . 146
5.2 The Macro Dimension. The Supra-Groups . . . . . . . . . . . . . . . . . . . 151
5.3 The Micro Dimension. The Regions . . . . . . . . . . . . . . . . . . . . . . . . 159
5.3.1 Moldova . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
5.3.2 Muntenia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
5.3.3 Oltenia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
5.3.4 Central Serbia and Vojvodina . . . . . . . . . . . . . . . . . . . . . . . 163
5.3.5 North-West Thrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
5.3.6 Transylvania . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171
Contents xi
6 The Overall Picture. Concluding Interpretations . . . . . . . . . . . . . . . . 175
6.1 Correspondence to Earlier Statistical Study . . . . . . . . . . . . . . . . . . 175
6.2 Identity and Political Development in the Late Iron Age
of the Eastern Carpathian Basin and the Lower Danube . . . . . . . . . 179
6.3 Ethnicity in the Late Iron Age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
6.3.1 T he Issue of Ethnicity in the Iron Age . . . . . . . . . . . . . . . . . 189
6.3.2 T he Getae and Dacian Correspondence . . . . . . . . . . . . . . . . 191
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
Annex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269
